{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T17:18:32Z","timestamp":1785172712884,"version":"3.55.0"},"reference-count":62,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"R01 grant","award":["1R01HD117563"],"award-info":[{"award-number":["1R01HD117563"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Magnetic resonance imaging (MRI) has become the gold standard for evaluating brain injury and development in newborn infants, providing structural, metabolic, and functional information without ionizing radiation. This review comprehensively examines the principal MRI modalities used in current neonatal neuroimaging for a novice\/intermediate-level reader\u2014including conventional T1- and T2-weighted imaging, diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping, diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), susceptibility-weighted imaging (SWI), volumetric analysis, arterial spin labeling (ASL), and functional connectivity MRI\u2014with particular attention to their applications in preterm and term populations. Additionally, validated MRI scoring systems for quantifying brain injury severity and predicting neurodevelopmental outcomes are reviewed and summarized. Understanding the technical principles, clinical applications, and limitations of these modalities is essential for optimal interpretation of neonatal brain MRI, and for advancing prognostication and therapeutic decision-making in this vulnerable population.<\/jats:p>","DOI":"10.3390\/bioengineering13080859","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T16:11:56Z","timestamp":1785168716000},"page":"859","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Magnetic Resonance Imaging of the Neonatal Brain: Modalities, Scoring Systems, and Clinical Applications"],"prefix":"10.3390","volume":"13","author":[{"given":"Swathi","family":"Ariyapadi","sequence":"first","affiliation":[{"name":"Division of Newborn Medicine, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"},{"name":"Center for Perinatal and Infant Research, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"},{"name":"Department of Pediatrics, University of California, Irvine, CA 92868, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily","family":"Garavatti","sequence":"additional","affiliation":[{"name":"Center for Perinatal and Infant Research, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"},{"name":"Department of Pediatrics, University of California, Irvine, CA 92868, USA"},{"name":"Division of Neurology, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Terrie","family":"Inder","sequence":"additional","affiliation":[{"name":"Division of Newborn Medicine, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"},{"name":"Center for Perinatal and Infant Research, Rady Children\u2019s Hospital of Orange County, Orange, CA 92868, USA"},{"name":"Department of Pediatrics, University of California, Irvine, CA 92868, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18221","DOI":"10.1038\/s41598-025-02539-1","article-title":"CMRI-detected Brain Injuries and Clinical Key Risk Factors Associated with Adverse Neurodevelopmental Outcomes in Very Preterm Infants","volume":"15","author":"Drommelschmidt","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e2020029082","DOI":"10.1542\/peds.2020-029082","article-title":"Routine Neuroimaging of the Preterm Brain","volume":"146","author":"Hand","year":"2020","journal-title":"Pediatrics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1002\/jmri.27192","article-title":"MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances","volume":"53","author":"Dubois","year":"2021","journal-title":"J. Magn. Reson. Imaging"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1300","DOI":"10.1007\/s00247-022-05550-0","article-title":"Magnetic Resonance Imaging in Neonates: A Practical Approach to Optimize Image Quality and Increase Diagnostic Yield","volume":"53","author":"Handa","year":"2023","journal-title":"Pediatr. Radiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1001\/jamapediatrics.2014.3269","article-title":"Hypoxic-Ischemic Encephalopathy: A Review for the Clinician","volume":"169","author":"Weiss","year":"2015","journal-title":"JAMA Pediatr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e2025073627","DOI":"10.1542\/peds.2025-073627","article-title":"Therapeutic Hypothermia for Neonatal Hypoxic-Ischemic Encephalopathy: Clinical Report","volume":"157","author":"Zanelli","year":"2026","journal-title":"Pediatrics"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1001\/jamapediatrics.2024.6209","article-title":"NICHD Magnetic Resonance Brain Imaging Score in Term Infants with Hypoxic-Ischemic Encephalopathy: A Secondary Analysis of a Randomized Clinical Trial","volume":"179","author":"Shankaran","year":"2025","journal-title":"JAMA Pediatr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1038\/pr.2016.195","article-title":"Fifty Years of Brain Imaging in Neonatal Encephalopathy Following Perinatal Asphyxia","volume":"81","author":"Groenendaal","year":"2017","journal-title":"Pediatr. Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Laptook, A., Garvey, A.A., Adams, C., Grant, P.E., Molloy, E.J., Groenendaal, F., Weeke, L.C., Benders, M., Hwang, M., and El-Dib, M. (2025). Magnetic Resonance Imaging and Spectroscopy in Neonatal Encephalopathy: Current Consensus Position and Future Opportunities. Pediatr. Res., 1\u201315.","DOI":"10.1038\/s41390-025-04448-5"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"American College of Obstetricians and Gynecologists (2014). Executive Summary: Neonatal Encephalopathy and Neurologic Outcome, Second Edition. Report of the American College of Obstetricians and Gynecologists\u2019 Task Force on Neonatal Encephalopathy. Obstet. Gynecol., 123, 896\u2013901.","DOI":"10.1097\/01.AOG.0000445580.65983.d2"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1159\/000499346","article-title":"Neurodevelopmental Outcomes in Preterm Infants with White Matter Injury Using a New MRI Classification","volume":"116","author":"Groenendaal","year":"2019","journal-title":"Neonatology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e214016","DOI":"10.1212\/WNL.0000000000214016","article-title":"Association of Early-Life or Term-Equivalent White Matter Injury with Neurodevelopmental Outcomes in Very Preterm Infants","volume":"105","author":"Selvanathan","year":"2025","journal-title":"Neurology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jpeds.2021.01.008","article-title":"Diffusion Tensor Imaging in Very Preterm, Moderate-Late Preterm and Term-Born Neonates: A Systematic Review","volume":"232","author":"Dibble","year":"2021","journal-title":"J. Pediatr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1159\/000530938","article-title":"Quantification of Diffusion Magnetic Resonance Imaging for Prognostic Prediction of Neonatal Hypoxic-Ischemic Encephalopathy","volume":"46","author":"Onda","year":"2024","journal-title":"Dev. Neurosci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2034","DOI":"10.3174\/ajnr.A7328","article-title":"A Uniform Description of Perioperative Brain MRI Findings in Infants with Severe Congenital Heart Disease: Results of a European Collaboration","volume":"42","author":"Stegeman","year":"2021","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"119815","DOI":"10.1016\/j.neuroimage.2022.119815","article-title":"Early Brain Morphometrics From Neonatal MRI Predict Motor and Cognitive Outcomes at 2-Years Corrected Age in Very Preterm Infants","volume":"267","author":"Pagnozzi","year":"2023","journal-title":"NeuroImage"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Beare, R.J., Chen, J., Kelly, C.E., Alexopoulos, D., Smyser, C.D., Rogers, C.E., Loh, W.Y., Matthews, L.G., Cheong, J.L., and Spittle, A.J. (2016). Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation. Front. Neuroinform., 10.","DOI":"10.3389\/fninf.2016.00012"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1136\/archdischild-2021-322846","article-title":"MRI-based Brain Volumes of Preterm Infants at Term: A Systematic Review and Meta-Analysis","volume":"107","author":"Romberg","year":"2022","journal-title":"Arch. Dis. Child.-Fetal Neonatal Ed."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1002\/ana.410430213","article-title":"Quantitative Magnetic Resonance Imaging of Brain Development in Premature and Mature Newborns","volume":"43","author":"Warfield","year":"1998","journal-title":"Ann. Neurol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1056\/NEJMra2303347","article-title":"Defining the Neurologic Consequences of Preterm Birth","volume":"389","author":"Inder","year":"2023","journal-title":"N. Engl. J. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1007\/s00247-023-05620-x","article-title":"An Automatic and Accurate Deep Learning-Based Neuroimaging Pipeline for the Neonatal Brain","volume":"53","author":"Shen","year":"2023","journal-title":"Pediatr. Radiol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e220088","DOI":"10.1148\/rg.220088","article-title":"Arterial Spin Labeling: Techniques, Clinical Applications, and Interpretation","volume":"43","author":"Iutaka","year":"2023","journal-title":"Radiographics"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1370","DOI":"10.1007\/s00247-022-05288-9","article-title":"A Practical Guide to Optimize Arterial Spin Labeling in Neonates at 1.5 Tesla: What the Radiologist Needs to Know","volume":"52","author":"Delmas","year":"2022","journal-title":"Pediatr. Radiol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"101130","DOI":"10.1016\/j.siny.2020.101130","article-title":"Arterial Spin Labeling Perfusion in Neonates","volume":"25","author":"Tortora","year":"2020","journal-title":"Semin. Fetal Neonatal Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"100799","DOI":"10.1016\/j.spen.2020.100799","article-title":"Arterial Spin Labeling in Pediatric Neuroimaging","volume":"33","author":"Narayanan","year":"2020","journal-title":"Semin. Pediatr. Neurol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"121511","DOI":"10.1016\/j.neuroimage.2025.121511","article-title":"Comparative Evaluation of Single- and Multi-Delay Arterial Spin Labeling MRI in Preterm Neonates","volume":"321","author":"Prysiazhniuk","year":"2025","journal-title":"NeuroImage"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1002\/jmri.29740","article-title":"High-Fidelity MRI Assessment of Cerebral Perfusion in Healthy Neonates Less Than 1 Week of Age","volume":"62","author":"Hu","year":"2025","journal-title":"J. Magn. Reson. Imaging"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1038\/s41372-025-02486-9","article-title":"MRI Scoring Systems in Neonatal Encephalopathy and Neurodevelopmental Outcomes: A Systematic Review","volume":"46","author":"Finnegan","year":"2025","journal-title":"J. Perinatol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1038\/s41390-024-03189-1","article-title":"The Predictive Value of MRI Scores for Neurodevelopmental Outcome in Infants with Neonatal Encephalopathy","volume":"97","author":"Andorka","year":"2025","journal-title":"Pediatr. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1038\/s41390-023-02510-8","article-title":"How Well Does Neonatal Neuroimaging Correlate with Neurodevelopmental Outcomes in Infants with Hypoxic-Ischemic Encephalopathy?","volume":"94","author":"Wu","year":"2023","journal-title":"Pediatr. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1111\/dmcn.15453","article-title":"Mammillary Body Abnormalities and Cognitive Outcomes in Children Cooled for Neonatal Encephalopathy","volume":"65","author":"Spencer","year":"2023","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"5017","DOI":"10.1038\/s41598-021-83982-8","article-title":"Mammillary Body Atrophy and Other MRI Correlates of School-Age Outcome Following Neonatal Hypoxic-Ischemic Encephalopathy","volume":"11","author":"Annink","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.jpeds.2021.02.005","article-title":"Associations Between Neonatal Magnetic Resonance Imaging and Short- and Long-Term Neurodevelopmental Outcomes in a Longitudinal Cohort of Very Preterm Children","volume":"234","author":"Jansen","year":"2021","journal-title":"J. Pediatr."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1056\/NEJMoa053792","article-title":"Neonatal MRI to Predict Neurodevelopmental Outcomes in Preterm Infants","volume":"355","author":"Woodward","year":"2006","journal-title":"N. Engl. J. Med."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Brouwer, M.J., Kersbergen, K.J., van Kooij, B.J.M., Benders, M.J.N.L., van Haastert, I.C., Koopman-Esseboom, C., Neil, J.J., de Vries, L.S., Kidokoro, H., and Inder, T.E. (2016). Preterm Brain Injury on Term-Equivalent Age MRI in Relation to Perinatal Factors and Neurodevelopmental Outcome at Two Years. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0177128"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Bonezzi, L., Biagioni, T., Fiori, S., Luke, C., George, J.M., Colditz, P.B., Fripp, J., Ware, R.S., Pannek, K., and Boyd, R.N. (2026). Concordance and Association of Kidokoro MRI Scores at 32 and 40 Weeks Post-Menstrual Age with Neurodevelopmental Outcomes in Very Preterm Infants. AJNR Am. J. Neuroradiol., ajnr.A9350.","DOI":"10.3174\/ajnr.A9350"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.jpeds.2017.04.059","article-title":"Associations of Newborn Brain Magnetic Resonance Imaging with Long-Term Neurodevelopmental Impairments in Very Preterm Children","volume":"187","author":"Anderson","year":"2017","journal-title":"J. Pediatr."},{"key":"ref_38","first-page":"e1231","article-title":"Predicting Developmental Outcomes in Preterm Infants: A Simple White Matter Injury Imaging Rule","volume":"93","author":"Guo","year":"2019","journal-title":"Neurology"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1212\/WNL.0000000000003606","article-title":"Quantitative Assessment of White Matter Injury in Preterm Neonates: Association with Outcomes","volume":"88","author":"Guo","year":"2017","journal-title":"Neurology"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"13250","DOI":"10.1038\/s41598-017-13753-x","article-title":"Punctate White Matter Lesions Associated with Altered Brain Development and Adverse Motor Outcome in Preterm Infants","volume":"7","author":"Tusor","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e209264","DOI":"10.1212\/WNL.0000000000209264","article-title":"Size and Location of Preterm Brain Injury and Associations with Neurodevelopmental Outcomes","volume":"102","author":"Selvanathan","year":"2024","journal-title":"Neurology"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1111\/dmcn.15116","article-title":"A Novel Magnetic Resonance Imaging-Based Scoring System to Predict Outcome in Neonates Born Preterm with Intraventricular Haemorrhage","volume":"64","author":"Goeral","year":"2022","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"101733","DOI":"10.1016\/j.siny.2026.101733","article-title":"Long-Term Neurodevelopmental Outcomes and Follow-Up of Germinal Matrix-Intraventricular Hemorrhage in Preterm Infants","volume":"31","author":"Leijser","year":"2026","journal-title":"Semin. Fetal Neonatal Med."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"101726","DOI":"10.1016\/j.siny.2026.101726","article-title":"Diagnostic Neuroimaging and Early Detection of Germinal Matrix Hemorrhage-Intraventricular Hemorrhage","volume":"31","author":"Cizmeci","year":"2026","journal-title":"Semin. Fetal Neonatal Med."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1161\/CIR.0b013e318265ee8a","article-title":"Neurodevelopmental Outcomes in Children with Congenital Heart Disease: Evaluation and Management: A Scientific Statement From the American Heart Association","volume":"126","author":"Marino","year":"2012","journal-title":"Circulation"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e997","DOI":"10.1161\/CIR.0000000000001211","article-title":"Neurodevelopmental Outcomes for Individuals with Congenital Heart Disease: Updates in Neuroprotection, Risk-Stratification, Evaluation, and Management: A Scientific Statement From the American Heart Association","volume":"149","author":"Sood","year":"2024","journal-title":"Circulation"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1986","DOI":"10.1016\/j.jacc.2018.02.068","article-title":"Neonatal Brain Injury and Timing of Neurodevelopmental Assessment in Patients with Congenital Heart Disease","volume":"71","author":"Peyvandi","year":"2018","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"105574","DOI":"10.1016\/j.earlhumdev.2022.105574","article-title":"Scoring of Brain Magnetic Resonance Imaging and Neurodevelopmental Outcomes in Infants with Congenital Heart Disease","volume":"169","author":"Bhattacharjee","year":"2022","journal-title":"Early Hum. Dev."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.3174\/ajnr.A6666","article-title":"MRI Findings at Term-Corrected Age and Neurodevelopmental Outcomes in a Large Cohort of Very Preterm Infants","volume":"41","author":"Arulkumaran","year":"2020","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1038\/s41390-018-0194-6","article-title":"Brain Imaging in Preterm Infants 32 Weeks Gestation: A Clinical Review and Algorithm for the Use of Cranial Ultrasound and Qualitative Brain MRI","volume":"84","author":"Ibrahim","year":"2018","journal-title":"Pediatr. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"117984","DOI":"10.1016\/j.neuroimage.2021.117984","article-title":"Early Diagnosis and Treatment of Infants with Prenatal and Perinatal Risk Factors for Brain Damage at the Neurodevelopmental Research Unit in Mexico","volume":"235","author":"Harmony","year":"2021","journal-title":"NeuroImage"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.clp.2013.10.003","article-title":"The Role of Neuroimaging in Predicting Neurodevelopmental Outcomes of Preterm Neonates","volume":"41","author":"Kwon","year":"2014","journal-title":"Clin. Perinatol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"11489","DOI":"10.1038\/s41598-023-38430-0","article-title":"Unsupervised Abnormality Detection in Neonatal MRI Brain Scans Using Deep Learning","volume":"13","author":"Raad","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"115033","DOI":"10.1016\/j.jpeds.2026.115033","article-title":"Neuroprognostication via Radiomics and Machine Learning Following Neonatal Hypoxic-Ischemic Insult","volume":"293","author":"Lewis","year":"2026","journal-title":"J. Pediatr."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1002\/ana.27154","article-title":"Automated Neuroprognostication via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy","volume":"97","author":"Lewis","year":"2025","journal-title":"Ann. Neurol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.neuroimage.2018.05.049","article-title":"A Computational Framework for the Detection of Subcortical Brain Dysmaturation in Neonatal MRI Using 3D Convolutional Neural Networks","volume":"178","author":"Ceschin","year":"2018","journal-title":"NeuroImage"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"13259","DOI":"10.1038\/s41598-023-40244-z","article-title":"Determining Regional Brain Growth in Premature and Mature Infants in Relation to Age at MRI Using Deep Neural Networks","volume":"13","author":"Beizaee","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2554","DOI":"10.1038\/s41390-025-04336-y","article-title":"Emerging Modalities for Neuroprognostication in Neonatal Encephalopathy: Harnessing the Potential of Artificial Intelligence","volume":"98","author":"Chawla","year":"2025","journal-title":"Pediatr. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"111627","DOI":"10.1016\/j.brainresbull.2025.111627","article-title":"Neuro-Multimodal Monitoring in Neonatal Brain Injury: Current Applications, Challenges, and Future Directions","volume":"233","author":"Wang","year":"2025","journal-title":"Brain Res. Bull."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"101346","DOI":"10.1016\/j.siny.2022.101346","article-title":"Application and Potential of Artificial Intelligence in Neonatal Medicine","volume":"27","author":"Kwok","year":"2022","journal-title":"Semin. Fetal Neonatal Med."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"e209861","DOI":"10.1212\/WNL.0000000000209861","article-title":"Common Critiques and Recommendations for Studies in Neurology Using ML Methods","volume":"103","author":"Speiser","year":"2024","journal-title":"Neurology"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"152100","DOI":"10.1016\/j.semperi.2025.152100","article-title":"Preserving Medical Ethics in the Era of Artificial Intelligence: Challenges and Opportunities in Neonatology","volume":"49","author":"Arora","year":"2025","journal-title":"Semin. Perinatol."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/8\/859\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T16:34:31Z","timestamp":1785170071000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/8\/859"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,25]]},"references-count":62,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["bioengineering13080859"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering13080859","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,25]]}}}