{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T19:48:46Z","timestamp":1790884126859,"version":"4.1.0"},"reference-count":137,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:p>Thyroid nodules are highly prevalent, with increasing detection rates driven by advanced imaging and expanded screening. Ultrasound serves as the first-line tool for screening, diagnosis and follow-up, owing to its non-invasiveness, real-time capability, cost-effectiveness and absence of ionizing radiation. However, conventional ultrasound diagnosis is highly operator-dependent, resulting in substantial inter-observer variability and diagnostic errors, particularly for subtle or indeterminate lesions. Artificial intelligence (AI), particularly deep learning and radiomics, has emerged as a promising approach to address these limitations by enabling automated feature extraction, quantitative analysis and standardized interpretation, which has the potential to improve diagnostic efficiency and risk stratification. This review summarizes AI applications in thyroid ultrasound, including image preprocessing, nodule segmentation, quantitative feature analysis, benign-malignant differentiation, TIRADS optimization and automated reporting. We highlight AI\u2019s potential in enhancing diagnostic consistency and accuracy, while critically assessing the methodological quality, bias risks and external validation of existing studies. Most AI tools are still in early translational phases, lacking large-scale validation in real clinical settings and standardized reporting protocols. We further discuss key challenges, including data bias, limited generalizability due to small or single-center datasets, poor interpretability and significant translational barriers. Future directions involving multi-modal fusion, explainable AI, real-time clinical systems and rigorous, multi-center standardized validation are proposed to facilitate clinical translation and improve patient care.<\/jats:p>","DOI":"10.3389\/fendo.2026.1877780","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T08:20:04Z","timestamp":1786436404000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial intelligence in thyroid ultrasound: clinical applications and perspectives"],"prefix":"10.3389","volume":"17","author":[{"given":"Ye","family":"Guo","sequence":"first","affiliation":[{"name":"Cancer Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Imaging Center, The Third Affiliated Hospital of Changchun University of Chinese Medicine","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ultrasound Diagnostic Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yansong","family":"Liu","sequence":"additional","affiliation":[{"name":"Ultrasound Diagnostic Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Hand and Foot Surgery, Orthopedics Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beibei","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Hand and Foot Surgery, Orthopedics Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiming","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Hand and Foot Surgery, Orthopedics Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiangbo","family":"Shao","sequence":"additional","affiliation":[{"name":"Ultrasound Diagnostic Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lirong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Ultrasound Diagnostic Center, The First Hospital of Jilin University","place":["Changchun, Jilin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,11]]},"reference":[{"key":"B1","article-title":"Thyroiditis","volume":"73","author":"Bindra","year":"2006","journal-title":"Am Fam Physician"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.575166","article-title":"Deep learning based on ACR TI-RADS can improve the differential diagnosis of thyroid nodules","volume":"11","author":"Wu","year":"2021","journal-title":"Front Oncol"},{"key":"B3","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1186\/s12885-025-13847-0","article-title":"Pilot study of ultrasound-guided microwave ablation for inactivating excess remnant thyroid after surgery in patients with differentiated thyroid cancer","volume":"25","author":"Chen","year":"2025","journal-title":"BMC Cancer"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2025.1551983","article-title":"Integrating shear wave elastography into clinical prediction of Graves\u2019 disease recurrence: a novel risk scoring system","volume":"16","author":"Zha","year":"2025","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.12659\/MSM.945793","article-title":"Arrival-time parametric imaging in contrast-enhanced ultrasound for thyroid nodule differentiation","volume":"30","author":"Jiang","year":"2024","journal-title":"Med Sci Monit"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28553","article-title":"Three-dimensional whole-brain simultaneous T1, T2, and T1\u03c1 quantification using MR multitasking: method and initial clinical experience in tissue characterization of multiple sclerosis","volume":"85","author":"Ma","year":"2021","journal-title":"Magn Reson Med"},{"key":"B7","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1186\/s12891-018-2153-0","article-title":"A randomised controlled trial of the clinical and cost-effectiveness of ultrasound-guided intra-articular corticosteroid and local anaesthetic injections: the hip injection trial (HIT) protocol","volume":"19","author":"Paskins","year":"2018","journal-title":"BMC Musculoskelet Disord"},{"key":"B8","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1186\/s12959-025-00797-7","article-title":"Molecular diagnosis of inherited platelet disorders: a tale of two realities - advanced vs. resource-limited setting","volume":"23","author":"Safdari","year":"2025","journal-title":"Thromb J"},{"key":"B9","doi-asserted-by":"publisher","first-page":"24216","DOI":"10.1038\/s41598-024-75677-7","article-title":"Diagnostic sensitivity of fine-needle aspiration cytology in thyroid cancer","volume":"14","author":"Lind","year":"2024","journal-title":"Sci Rep"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1200\/OP.23.00037","article-title":"Optimizing outpatient radiation oncology consult workflow by using time-driven activity-based costing: efficiency and financial impacts","volume":"20","author":"Weng","year":"2024","journal-title":"JCO Oncol Pract"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.918900","article-title":"Next-generation pathology using multiplexed immunohistochemistry: mapping tissue architecture at single-cell level","volume":"12","author":"Bosisio","year":"2022","journal-title":"Front Oncol"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23084156","article-title":"Cytomolecular classification of thyroid nodules using fine-needle washes aspiration biopsies","volume":"23","author":"Capitoli","year":"2022","journal-title":"Int J Mol Sci"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2023.958310","article-title":"Applications of machine and deep learning to thyroid cytology and histopathology: a review","volume":"13","author":"Slabaugh","year":"2023","journal-title":"Front Oncol"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e26062","article-title":"Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection","volume":"10","author":"Li","year":"2024","journal-title":"Heliyon"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.70319","article-title":"Discrimination of benign and Malignant non-mass breast lesions using ultrasound radiomics with machine learning models","volume":"27","author":"Shi","year":"2026","journal-title":"J Appl Clin Med Phys"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.3389\/fradi.2024.1460889","article-title":"SenseCare: a research platform for medical image informatics and interactive 3D visualization","volume":"4","author":"Wang","year":"2024","journal-title":"Front Radiol"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1007\/s10554-024-03256-y","article-title":"Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: diagnostic performance and limitations","volume":"40","author":"K\u00fcbler","year":"2024","journal-title":"Int J Cardiovasc Imaging"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1002\/jcu.24058","article-title":"An ultrasound image-based deep learning radiomics nomogram for differentiating between benign and Malignant indeterminate cytology (Bethesda III) thyroid nodules: a retrospective study","volume":"53","author":"Zhong","year":"2025","journal-title":"J Clin Ultrasound"},{"key":"B19","doi-asserted-by":"publisher","first-page":"15412","DOI":"10.1038\/s41598-025-00331-9","article-title":"Smart weed recognition in saffron fields based on an improved EfficientNetB0 model and RGB images","volume":"15","author":"Makarian","year":"2025","journal-title":"Sci Rep"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1093\/nsr\/nwad298","article-title":"Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications","volume":"11","author":"Pyun","year":"2024","journal-title":"Natl Sci Rev"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2025.1525285","article-title":"Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy","volume":"15","author":"Tenghui","year":"2025","journal-title":"Front Oncol"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1080\/0886022X.2024.2329249","article-title":"Tiny clue reveals the general trend: a bibliometric and visualized analysis of renal microcirculation","volume":"46","author":"Wang","year":"2024","journal-title":"Ren Fail"},{"key":"B23","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1186\/s12916-024-03742-z","article-title":"Comparison of MRI artificial intelligence-guided cognitive fusion-targeted biopsy versus routine cognitive fusion-targeted prostate biopsy in prostate cancer diagnosis: a randomized controlled trial","volume":"22","author":"Deng","year":"2024","journal-title":"BMC Med"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2024.1501652","article-title":"Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology","volume":"11","author":"Lyu","year":"2024","journal-title":"Front Med (Lausanne)"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocae165","article-title":"Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging","volume":"31","author":"Stanley","year":"2024","journal-title":"J Am Med Inform Assoc"},{"key":"B26","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s12880-024-01222-7","article-title":"Combining radiomics with thyroid imaging reporting and data system to predict lateral cervical lymph node metastases in medullary thyroid cancer","volume":"24","author":"Liu","year":"2024","journal-title":"BMC Med Imaging"},{"key":"B27","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1021\/acschemneuro.5c00543","article-title":"Machine learning for neurotransmitter monitoring by fast voltammetry: current and future prospects","volume":"17","author":"Movassaghi","year":"2026","journal-title":"ACS Chem Neurosci"},{"key":"B28","doi-asserted-by":"publisher","first-page":"15072","DOI":"10.1038\/s41598-020-71914-x","article-title":"A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants","volume":"10","author":"He","year":"2020","journal-title":"Sci Rep"},{"key":"B29","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1186\/s12891-025-08846-y","article-title":"Automated radiographic assessment of lower limb alignment using deep learning in a data-constrained clinical setting","volume":"26","author":"H\u00e4fliger","year":"2025","journal-title":"BMC Musculoskelet Disord"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.3390\/s23177614","article-title":"Explainable convolutional neural networks for brain cancer detection and localisation","volume":"23","author":"Mercaldo","year":"2023","journal-title":"Sensors (Basel)"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12112644","article-title":"Artificial intelligence in lung cancer imaging: unfolding the future","volume":"12","author":"Cellina","year":"2022","journal-title":"Diagnostics (Basel)"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13142463","article-title":"A deep learning framework for the characterization of thyroid nodules from ultrasound images using improved inception network and multi-level transfer learning","volume":"13","author":"Ajilisa","year":"2023","journal-title":"Diagnostics (Basel)"},{"key":"B33","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1186\/s12880-024-01415-0","article-title":"Enhanced pediatric thyroid ultrasound image segmentation using DC-Contrast U-Net","volume":"24","author":"Peng","year":"2024","journal-title":"BMC Med Imaging"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13040617","article-title":"PathoFusion: an open-source AI framework for recognition of pathomorphological features and mapping of immunohistochemical data","volume":"13","author":"Bao","year":"2021","journal-title":"Cancers (Basel)"},{"key":"B35","doi-asserted-by":"publisher","first-page":"16576","DOI":"10.1038\/s41598-025-98454-6","article-title":"AI-IoT based smart agriculture pivot for plant diseases detection and treatment","volume":"15","author":"Ibrahim","year":"2025","journal-title":"Sci Rep"},{"key":"B36","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1186\/s12880-025-01703-3","article-title":"Multiple deep learning models based on MRI images in discriminating glioblastoma from solitary brain metastases: a multicentre study","volume":"25","author":"Kong","year":"2025","journal-title":"BMC Med Imaging"},{"key":"B37","doi-asserted-by":"publisher","first-page":"6501","DOI":"10.1038\/s41598-025-91364-7","article-title":"Enhanced recognition and counting of high-coverage Amorphophallus konjac by integrating UAV RGB imagery and deep learning","volume":"15","author":"Yang","year":"2025","journal-title":"Sci Rep"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0329963","article-title":"Automated classification of clinical diagnoses in electronic health records using transformer","volume":"20","author":"Dai","year":"2025","journal-title":"PloS One"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1117\/1.JBO.27.10.106004","article-title":"Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging","volume":"27","author":"Madasamy","year":"2022","journal-title":"J BioMed Opt"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1002\/mp.70003","article-title":"Multi-scale nested graph transformer with graph operations: advancing high-resolution chest x-ray classification","volume":"52","author":"Shan","year":"2025","journal-title":"Med Phys"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.20080","article-title":"Emerging applications of radiomics in neurological disorders: a review","volume":"13","author":"Sotoudeh","year":"2021","journal-title":"Cureus"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2024-092594","article-title":"Development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data: a protocol","volume":"15","author":"Deng","year":"2025","journal-title":"BMJ Open"},{"key":"B43","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1186\/s12880-025-01743-9","article-title":"Radiomics and machine learning for osteoporosis detection using abdominal computed tomography: a retrospective multicenter study","volume":"25","author":"Liu","year":"2025","journal-title":"BMC Med Imaging"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.1016\/j.jot.2023.10.003","article-title":"Radiomics signature of osteoarthritis: current status and perspective","volume":"45","author":"Jiang","year":"2024","journal-title":"J Orthop Translat"},{"key":"B45","doi-asserted-by":"publisher","first-page":"95","DOI":"10.14366\/usg.24152","article-title":"Ultrasound-based radiogenomics: status, applications, and future direction","volume":"44","author":"Wang","year":"2025","journal-title":"Ultrasonography"},{"key":"B46","doi-asserted-by":"publisher","DOI":"10.7150\/ijms.79758","article-title":"Multiclassifier radiomics analysis of ultrasound for prediction of extrathyroidal extension in papillary thyroid carcinoma in children","volume":"20","author":"Li","year":"2023","journal-title":"Int J Med Sci"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.1007\/s11547-024-01768-0","article-title":"Ultrasound-based radiomics nomogram for predicting axillary lymph node metastasis in early-stage breast cancer","volume":"129","author":"Zhang","year":"2024","journal-title":"Radiol Med"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2023.108394","article-title":"Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy","volume":"26","author":"Yang","year":"2023","journal-title":"iScience"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.7215","article-title":"Researching mental health disorders in the era of social media: systematic review","volume":"19","author":"Wongkoblap","year":"2017","journal-title":"J Med Internet Res"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.3390\/cancers11111759","article-title":"The diagnostic efficiency of ultrasound computer-aided diagnosis in differentiating thyroid nodules: a systematic review and narrative synthesis","volume":"11","author":"Chambara","year":"2019","journal-title":"Cancers (Basel)"},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2025.11.665","article-title":"Deep learning for ultrasound-based auxiliary diagnosis of emergency ascites","author":"Wang","year":"2026","journal-title":"Ultrasound Med Biol"},{"key":"B52","doi-asserted-by":"publisher","first-page":"23997","DOI":"10.1038\/s41598-024-75174-x","article-title":"A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults","volume":"14","author":"Djaballah","year":"2024","journal-title":"Sci Rep"},{"key":"B53","doi-asserted-by":"publisher","DOI":"10.1055\/s-0043-1764425","article-title":"Developing an artificial intelligence solution to autosegment the edentulous mandibular bone for implant planning","volume":"17","author":"Moufti","year":"2023","journal-title":"Eur J Dent"},{"key":"B54","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1186\/s12880-024-01244-1","article-title":"The value of a neural network based on multi-scale feature fusion to ultrasound images for the differentiation in thyroid follicular neoplasms","volume":"24","author":"Chen","year":"2024","journal-title":"BMC Med Imaging"},{"key":"B55","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1016\/j.cels.2020.04.003","article-title":"nucleAIzer: A parameter-free deep learning framework for nucleus segmentation using image style transfer","volume":"10","author":"Hollandi","year":"2020","journal-title":"Cell Syst"},{"key":"B56","doi-asserted-by":"publisher","DOI":"10.3348\/kjr.2021.0772","article-title":"Diagnostic performance of core needle biopsy for characterizing thyroidectomy bed lesions","volume":"23","author":"Jeong","year":"2022","journal-title":"Korean J Radiol"},{"key":"B57","doi-asserted-by":"publisher","DOI":"10.3390\/curroncol31090374","article-title":"A novel deep learning model for breast tumor ultrasound image classification with lesion region perception","volume":"31","author":"Wei","year":"2024","journal-title":"Curr Oncol"},{"key":"B58","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.16773","article-title":"Automatic detection of Opisthorchis viverrini egg in stool examination using convolutional-based neural networks","volume":"12","author":"Thanchomnang","year":"2024","journal-title":"PeerJ"},{"key":"B59","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging10080193","article-title":"Revolutionizing cardiac imaging: A scoping review of artificial intelligence in echocardiography, CTA, and cardiac MRI","volume":"10","author":"Moradi","year":"2024","journal-title":"J Imaging"},{"key":"B60","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-10-70","article-title":"Automatic de-identification of textual documents in the electronic health record: a review of recent research","volume":"10","author":"Meystre","year":"2010","journal-title":"BMC Med Res Methodol"},{"key":"B61","doi-asserted-by":"publisher","DOI":"10.3389\/fbinf.2023.1229052","article-title":"Artificial intelligence in imaging flow cytometry","volume":"3","author":"Pozzi","year":"2023","journal-title":"Front Bioinform"},{"key":"B62","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.7.1.016502","article-title":"Integrating AI into radiology workflow: levels of research, production, and feedback maturity","volume":"7","author":"Dikici","year":"2020","journal-title":"J Med Imaging (Bellingham)"},{"key":"B63","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1038\/s41398-025-03367-7","article-title":"Bioenergetic biomarkers as predictive indicators and their relationship with cognitive function in newly diagnosed, drug-na\u00efve patients with bipolar disorder","volume":"15","author":"Cao","year":"2025","journal-title":"Transl Psychiatry"},{"key":"B64","doi-asserted-by":"publisher","first-page":"2136","DOI":"10.1007\/s12672-025-03957-3","article-title":"Development and validation of nomograms for distant metastasis and prognosis of small intestinal neuroendocrine tumors","volume":"16","author":"Xu","year":"2025","journal-title":"Discov Oncol"},{"key":"B65","doi-asserted-by":"publisher","first-page":"39722","DOI":"10.1038\/s41598-025-23263-w","article-title":"Four-class classification of tumor-induced colorectal obstruction histopathology: A ResNet-mamba-mased study on cellular interaction pattern recognition","volume":"15","author":"Du","year":"2025","journal-title":"Sci Rep"},{"key":"B66","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000738","article-title":"Significant reduction in manual annotation costs in ultrasound medical image database construction through step by step artificial intelligence pre-annotation","volume":"4","author":"Zheng","year":"2025","journal-title":"PloS Digit Health"},{"key":"B67","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare10112262","article-title":"ESTAN: Enhanced small tumor-aware network for breast ultrasound image segmentation","volume":"10","author":"Shareef","year":"2022","journal-title":"Healthcare (Basel)"},{"key":"B68","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1186\/s12911-024-02695-w","article-title":"A time series algorithm to predict surgery in neonatal necrotizing enterocolitis","volume":"24","author":"Cui","year":"2024","journal-title":"BMC Med Inform Decis Mak"},{"key":"B69","doi-asserted-by":"publisher","DOI":"10.1097\/JCMA.0000000000001273","article-title":"Evaluating GPT-4\u2019s visual interpretation and clinical reasoning on emergency settings: A 5-year analysis","volume":"88","author":"Wang","year":"2025","journal-title":"J Chin Med Assoc"},{"key":"B70","doi-asserted-by":"publisher","DOI":"10.3348\/kjr.2021.0106","article-title":"Korean thyroid imaging reporting and data system: Current status, challenges, and future perspectives","volume":"22","author":"Ha","year":"2021","journal-title":"Korean J Radiol"},{"key":"B71","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2025.1629637","article-title":"DualPlaqueNet with dual-branch structure and attention mechanism for carotid plaque semantic segmentation and size prediction","volume":"16","author":"Deng","year":"2025","journal-title":"Front Physiol"},{"key":"B72","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15133267","article-title":"Recent advances in deep learning and medical imaging for head and neck cancer treatment: MRI, CT, and PET scans","volume":"15","author":"Illimoottil","year":"2023","journal-title":"Cancers (Basel)"},{"key":"B73","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2025.1576461","article-title":"Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review","volume":"15","author":"Haixian","year":"2025","journal-title":"Front Oncol"},{"key":"B74","doi-asserted-by":"publisher","DOI":"10.1186\/s13089-025-00451-3","article-title":"Evaluating deep learning approaches for AI-assisted lung ultrasound diagnosis: an international multi-center and multi-scanner study","volume":"17","author":"Mu\u00f1oz","year":"2025","journal-title":"Ultrasound J"},{"key":"B75","doi-asserted-by":"publisher","DOI":"10.25259\/JCIS_99_2022","article-title":"Imaging of penetrating vascular trauma of the body and extremities secondary to ballistic and stab wounds","volume":"13","author":"Gopireddy","year":"2023","journal-title":"J Clin Imaging Sci"},{"key":"B76","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2024.1445069","article-title":"Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia","volume":"11","author":"Niu","year":"2024","journal-title":"Front Med (Lausanne)"},{"key":"B77","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107898","article-title":"MLMSeg: A multi-view learning model for ultrasound thyroid nodule segmentation","volume":"169","author":"Chen","year":"2024","journal-title":"Comput Biol Med"},{"key":"B78","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106389","article-title":"Thyroid region prior guided attention for ultrasound segmentation of thyroid nodules","volume":"155","author":"Gong","year":"2023","journal-title":"Comput Biol Med"},{"key":"B79","doi-asserted-by":"publisher","DOI":"10.1186\/s13040-025-00440-1","article-title":"Advancing preeclampsia prediction: a tailored machine learning pipeline integrating resampling and ensemble models for handling imbalanced medical data","volume":"18","author":"Ma","year":"2025","journal-title":"Biodata Min"},{"key":"B80","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2025.1552479","article-title":"A machine learning-based model for predicting recurrence in intermediate- and high-risk differentiated thyroid cancer: insights from a retrospective single-center study of 2388 patients","volume":"16","author":"Li","year":"2025","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B81","doi-asserted-by":"publisher","DOI":"10.21037\/gs-24-119","article-title":"Prediction of Malignant risk stratification model for parotid gland nodules based on clinical and conventional ultrasound features: construction and validation","volume":"13","author":"Gao","year":"2024","journal-title":"Gland Surg"},{"key":"B82","doi-asserted-by":"publisher","DOI":"10.1007\/s40477-024-00972-y","article-title":"TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review","volume":"28","author":"Sharifi","year":"2025","journal-title":"J Ultrasound"},{"key":"B83","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1186\/s40644-025-00944-3","article-title":"Malignancy prediction for calcified thyroid nodules using deep learning based on ultrasound dynamic videos","volume":"25","author":"Qian","year":"2025","journal-title":"Cancer Imaging"},{"key":"B84","doi-asserted-by":"publisher","first-page":"22","DOI":"10.3348\/kjr.2022.0894","article-title":"Standardized imaging and reporting for thyroid ultrasound: Korean Society of Thyroid Radiology consensus statement and recommendation","volume":"24","author":"Lee","year":"2023","journal-title":"Korean J Radiol"},{"key":"B85","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2023.1106281","article-title":"Comparison of primary hepatic neuroendocrine tumors and non-hepatitis B non-hepatitis C hepatocellular carcinoma on contrast-enhanced ultrasound","volume":"13","author":"Tan","year":"2023","journal-title":"Front Oncol"},{"key":"B86","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1002\/agm2.12165","article-title":"Expert consensus on diagnosis and treatment for elderly with thyroid diseases in China (2021)","volume":"4","author":"Liu","year":"2021","journal-title":"Aging Med (Milton)"},{"key":"B87","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000012728","article-title":"Ultrasonographic features of testicular metastasis from renal clear cell carcinoma that mimics a seminoma: A case report","volume":"97","author":"Huang","year":"2018","journal-title":"Med (Baltimore)"},{"key":"B88","doi-asserted-by":"publisher","first-page":"291","DOI":"10.2147\/JAA.S448064","article-title":"Study on predicting clinical stage of patients with bronchial asthma based on CT radiomics","volume":"17","author":"Chen","year":"2024","journal-title":"J Asthma Allergy"},{"key":"B89","doi-asserted-by":"publisher","DOI":"10.7863\/jum.2004.23.11.1455","article-title":"Risk for Malignancy of thyroid nodules as assessed by sonographic criteria: the need for biopsy","volume":"23","author":"Iannuccilli","year":"2004","journal-title":"J Ultrasound Med"},{"key":"B90","doi-asserted-by":"publisher","first-page":"7878","DOI":"10.1038\/s41598-024-58668-6","article-title":"The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules","volume":"14","author":"Zhang","year":"2024","journal-title":"Sci Rep"},{"key":"B91","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2022.878718","article-title":"A multi-scale densely connected convolutional neural network for automated thyroid nodule classification","volume":"16","author":"Wang","year":"2022","journal-title":"Front Neurosci"},{"key":"B92","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1186\/s13244-025-02035-0","article-title":"Interpretable and generalizable deep learning model for preoperative assessment of microvascular invasion and outcome in hepatocellular carcinoma based on MRI: a multicenter study","volume":"16","author":"Dong","year":"2025","journal-title":"Insights Imaging"},{"key":"B93","doi-asserted-by":"publisher","DOI":"10.1530\/EJE-21-0094","article-title":"The diagnostic accuracy of fine-needle aspiration cytology for thyroid nodules is not affected by coexistent chronic autoimmune thyroiditis: results from a cyto-histological series of patients with indeterminate cytology","volume":"185","author":"Rotondi","year":"2021","journal-title":"Eur J Endocrinol"},{"key":"B94","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2025.1639017","article-title":"Multimodal radiomics model with triple -timepoint contrast-enhanced ultrasound for precise diagnosis of C-TIRADS 4 thyroid nodules","volume":"16","author":"Shao","year":"2025","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B95","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2025.111171","article-title":"Advances in medical image segmentation: A comprehensive survey with a focus on lumbar spine applications","volume":"198","author":"Kabil","year":"2025","journal-title":"Comput Biol Med"},{"key":"B96","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-019-0328-2","article-title":"Echogenic foci in thyroid nodules: diagnostic performance with combination of TIRADS and echogenic foci","volume":"19","author":"Ha","year":"2019","journal-title":"BMC Med Imaging"},{"key":"B97","doi-asserted-by":"publisher","DOI":"10.3389\/fcell.2021.719262","article-title":"AI-model for identifying pathologic myopia based on deep learning algorithms of myopic maculopathy classification and \u201cplus\u201d lesion detection in fundus images","volume":"9","author":"Lu","year":"2021","journal-title":"Front Cell Dev Biol"},{"key":"B98","doi-asserted-by":"publisher","DOI":"10.1111\/eci.14370","article-title":"Applications, challenges and future directions of artificial intelligence in cardio-oncology","author":"Ravera","year":"2025","journal-title":"Eur J Clin Invest"},{"key":"B99","doi-asserted-by":"publisher","DOI":"10.1016\/j.arthro.2025.02.038","article-title":"Artificial intelligence as a tool to mitigate administrative burden, optimize billing, reduce insurance- and credentialing-related expenses, and improve quality assurance within health care systems","volume":"41","author":"Lavoie-Gagne","year":"2025","journal-title":"Arthroscopy"},{"key":"B100","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1186\/s12880-025-01679-0","article-title":"Ultrasonographic differentiation of medullary thyroid carcinoma from papillary thyroid carcinoma: quantitative comparison of morphologic features and different TIRADS risk categorizations","volume":"25","author":"Li","year":"2025","journal-title":"BMC Med Imaging"},{"key":"B101","doi-asserted-by":"publisher","DOI":"10.3389\/fped.2023.1112074","article-title":"Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children","volume":"11","author":"Mc Cord-De Iaco","year":"2023","journal-title":"Front Pediatr"},{"key":"B102","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging11110390","article-title":"Next-generation advances in prostate cancer imaging and artificial intelligence applications","volume":"11","author":"Miao","year":"2025","journal-title":"J Imaging"},{"key":"B103","doi-asserted-by":"publisher","DOI":"10.3390\/medicina61040561","article-title":"The artificial intelligence-enhanced echocardiographic detection of congenital heart defects in the fetus: a mini-review","volume":"61","author":"Suha","year":"2025","journal-title":"Med (Kaunas)"},{"key":"B104","doi-asserted-by":"publisher","DOI":"10.1111\/pcn.13804","article-title":"Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: using a graph neural network","volume":"79","author":"Yokotani","year":"2025","journal-title":"Psychiatry Clin Neurosci"},{"key":"B105","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1007\/s10238-025-01989-1","article-title":"Integrative multi-omics profiling for early diagnosis, stratification and personalized management of chronic kidney disease: a new paradigm","volume":"26","author":"Li","year":"2025","journal-title":"Clin Exp Med"},{"key":"B106","doi-asserted-by":"publisher","DOI":"10.1007\/s12253-019-00754-6","article-title":"Pancreatic intraepithelial neoplasia (PanIN) as a morphologic marker of pancreatobiliary type of ampullary carcinoma","volume":"26","author":"Krishnamurthy","year":"2020","journal-title":"Pathol Oncol Res"},{"key":"B107","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14050484","article-title":"Harnessing of artificial intelligence for the diagnosis and prevention of hospital-acquired infections: a systematic review","volume":"14","author":"Baddal","year":"2024","journal-title":"Diagnostics (Basel)"},{"key":"B108","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0322854","article-title":"AISIM: evaluating impacts of user interface elements of an AI assisting tool","volume":"20","author":"Wiratchawa","year":"2025","journal-title":"PloS One"},{"key":"B109","doi-asserted-by":"publisher","DOI":"10.3390\/s25206363","article-title":"MSIMG: a density-aware multi-channel image representation method for mass spectrometry","volume":"25","author":"Zhang","year":"2025","journal-title":"Sensors (Basel)"},{"key":"B110","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2024.1456144","article-title":"Global research trends in the application of artificial intelligence in oncology care: a bibliometric study","volume":"14","author":"Xu","year":"2024","journal-title":"Front Oncol"},{"key":"B111","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s11883-025-01356-1","article-title":"AI in adipose imaging: revolutionizing visceral adipose tissue, ectopic fat, and cardiovascular risk assessment","volume":"27","author":"Kandi","year":"2025","journal-title":"Curr Atheroscler Rep"},{"key":"B112","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1038\/s41746-025-01971-x","article-title":"Generative AI costs in large healthcare systems, an example in revenue cycle","volume":"8","author":"Burns","year":"2025","journal-title":"NPJ Digit Med"},{"key":"B113","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.59906","article-title":"Use of artificial intelligence in triage in hospital emergency departments: a scoping review","volume":"16","author":"Tyler","year":"2024","journal-title":"Cureus"},{"key":"B114","doi-asserted-by":"publisher","DOI":"10.3390\/s24144457","article-title":"Advancing DIEP flap monitoring with optical imaging techniques: a narrative review","volume":"24","author":"Kim","year":"2024","journal-title":"Sensors (Basel)"},{"key":"B115","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2025.1520898","article-title":"AI-powered diagnosis of ovarian conditions: insights from a newly introduced ultrasound dataset","volume":"16","author":"Borna","year":"2025","journal-title":"Front Physiol"},{"key":"B116","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.68472","article-title":"The role of artificial intelligence and machine learning in cardiovascular imaging and diagnosis","volume":"16","author":"Reza-Soltani","year":"2024","journal-title":"Cureus"},{"key":"B117","doi-asserted-by":"publisher","DOI":"10.3390\/metabo14040198","article-title":"Evolutive models, algorithms and predictive parameters for the progression of hepatic steatosis","volume":"14","author":"Tudor","year":"2024","journal-title":"Metabolites"},{"key":"B118","doi-asserted-by":"publisher","DOI":"10.1111\/jocd.70356","article-title":"Advances in longevity: the intersection of regenerative medicine and cosmetic dermatology","volume":"24","author":"Haykal","year":"2025","journal-title":"J Cosmet Dermatol"},{"key":"B119","doi-asserted-by":"publisher","DOI":"10.2196\/81328","article-title":"Detection and management of geographic atrophy secondary to age-related macular degeneration using noninvasive retinal images and artificial intelligence: systematic review","volume":"27","author":"Shi","year":"2025","journal-title":"J Med Internet Res"},{"key":"B120","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11040337","article-title":"The role of AI in hospitals and clinics: transforming healthcare in the 21st century","volume":"11","author":"Maleki Varnosfaderani","year":"2024","journal-title":"Bioengineering (Basel)"},{"key":"B121","doi-asserted-by":"publisher","first-page":"38042","DOI":"10.1038\/s41598-025-21888-5","article-title":"Enhancing lymphoma cancer detection using deep transfer learning on histopathological images","volume":"15","author":"Uppal","year":"2025","journal-title":"Sci Rep"},{"key":"B122","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1186\/s12911-025-03026-3","article-title":"Deep learning health space model for ordered responses","volume":"25","author":"Lee","year":"2025","journal-title":"BMC Med Inform Decis Mak"},{"key":"B123","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2025.1567545","article-title":"Preliminary exploratory study on differential diagnosis between benign and Malignant peripheral lung tumors: based on deep learning networks","volume":"12","author":"Wang","year":"2025","journal-title":"Front Med (Lausanne)"},{"key":"B124","doi-asserted-by":"publisher","first-page":"34081","DOI":"10.1038\/s41598-025-14169-8","article-title":"An optimized hybrid deep learning model to detect Alzheimer disease","volume":"15","author":"Raj","year":"2025","journal-title":"Sci Rep"},{"key":"B125","doi-asserted-by":"publisher","DOI":"10.3389\/fdgth.2025.1583490","article-title":"Application of artificial intelligence and machine learning in lung transplantation: a comprehensive review","volume":"7","author":"Liu","year":"2025","journal-title":"Front Digit Health"},{"key":"B126","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.1068418","article-title":"Iodine deficiency and real-life supplementation ineffectiveness in Polish pregnant women and its impact on thyroid metabolism","volume":"14","author":"Filipowicz","year":"2023","journal-title":"Front Endocrinol (Lausanne)"},{"key":"B127","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.54808","article-title":"Unveiling the intricacies: a comprehensive review of magnetic resonance imaging (MRI) assessment of T2-weighted hyperintensities in the neuroimaging landscape","volume":"16","author":"Dhabalia","year":"2024","journal-title":"Cureus"},{"key":"B128","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2023.1077605","article-title":"Multidisciplinary team diagnosis and treatment of pancreatic cancer: current landscape and future prospects","volume":"13","author":"Yao","year":"2023","journal-title":"Front Oncol"},{"key":"B129","doi-asserted-by":"publisher","DOI":"10.3390\/cancers16020311","article-title":"Integrated diagnostics of thyroid nodules","volume":"16","author":"Giovanella","year":"2024","journal-title":"Cancers (Basel)"},{"key":"B130","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1186\/s12960-021-00654-4","article-title":"Accreditation of private midwifery and nursing schools in Mali: a local sustainable solution to increasing the supply of qualified health workers","volume":"19","author":"Tour\u00e9","year":"2021","journal-title":"Hum Resour Health"},{"key":"B131","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.75476","article-title":"Differentiating cystic lesions in the sellar region of the brain using artificial intelligence and machine learning for early diagnosis: a prospective review of the novel diagnostic modalities","volume":"16","author":"Patel","year":"2024","journal-title":"Cureus"},{"key":"B132","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/0142159X.2025.2555353","article-title":"Enabling micro-assessments of skills in the simulated setting using temporal artificial intelligence-models","author":"Bang Andersen","year":"2025","journal-title":"Med Teach"},{"key":"B133","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2025.1523902","article-title":"Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study","volume":"12","author":"Xiao","year":"2025","journal-title":"Front Med (Lausanne)"},{"key":"B134","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12061384","article-title":"Diagnostic significance of FNAB miRNA expression in papillary thyroid carcinoma","volume":"12","author":"Laukien\u0117","year":"2022","journal-title":"Diagnostics (Basel)"},{"key":"B135","doi-asserted-by":"publisher","DOI":"10.2196\/85223","article-title":"AI in esophageal motility disorders: systematic review of high-resolution manometry studies","volume":"27","author":"Gong","year":"2025","journal-title":"J Med Internet Res"},{"key":"B136","doi-asserted-by":"publisher","DOI":"10.1016\/j.identj.2025.103910","article-title":"Diagnostic performance of large language models in multimodal analysis of radiolucent jaw lesions","volume":"75","author":"Kim","year":"2025","journal-title":"Int Dent J"},{"key":"B137","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2307952120","article-title":"Biosymbiotic platform for chronic long-range monitoring of biosignals in limited resource settings","volume":"120","author":"Stuart","year":"2023","journal-title":"Proc Natl Acad Sci USA"}],"container-title":["Frontiers in Endocrinology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2026.1877780\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T08:20:07Z","timestamp":1786436407000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fendo.2026.1877780\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,11]]},"references-count":137,"alternative-id":["10.3389\/fendo.2026.1877780"],"URL":"https:\/\/doi.org\/10.3389\/fendo.2026.1877780","relation":{},"ISSN":["1664-2392"],"issn-type":[{"value":"1664-2392","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,11]]},"article-number":"1877780"}}