{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T01:37:08Z","timestamp":1785893828507,"version":"3.56.0"},"reference-count":52,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:00:00Z","timestamp":1744156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Background and Objectives: Artificial intelligence has emerged as a transformative tool in healthcare, offering capabilities such as early diagnosis, personalised treatment, and real-time patient monitoring. In the context of rheumatoid arthritis, a chronic autoimmune disease that demands timely intervention, artificial intelligence shows promise in overcoming diagnostic delays and optimising disease management. This study examines the role of artificial intelligence in the diagnosis and management of rheumatoid arthritis, focusing on perceived benefits, challenges, and acceptance levels among healthcare professionals and patients. Materials and Methods: A cross-sectional study was conducted using a detailed questionnaire distributed to 205 participants, including rheumatologists, general practitioners, and rheumatoid arthritis patients from Romania. The study used descriptive statistics, chi-square tests, and logistic regression to analyse AI acceptance in rheumatology. Data visualisation and multiple imputations addressed missing values, ensuring accuracy. Statistical significance was set at p &lt; 0.05 for hypothesis testing. Results: Respondents with prior experience in artificial intelligence perceived it as more useful for early diagnosis and personalised management of RA (p &lt; 0.001). Familiarity with artificial intelligence concepts positively correlated with acceptance in routine rheumatology practice (\u03c1 = 1.066, p &lt; 0.001). The main barriers identified were high costs (36%), lack of medical staff training (37%), and concerns regarding diagnostic accuracy (21%). Although less frequently mentioned, data privacy concerns remained relevant for a subset of respondents. The study revealed that artificial intelligence could improve diagnostic accuracy and rheumatoid arthritis monitoring, being perceived as a valuable tool by professionals familiar with digital technologies. However, 42% of participants cited the lack of data standardisation across medical systems as a major barrier, underscoring the need for effective interoperability solutions. Conclusions: Artificial intelligence has the potential to revolutionise rheumatoid arthritis management through faster and more accurate diagnoses, personalised treatments, and optimised monitoring. Nevertheless, challenges such as costs, staff training, and data privacy need to be addressed to ensure efficient integration into clinical practice. Educational programmes and interdisciplinary collaboration are essential to increase artificial intelligence adoption in rheumatology.<\/jats:p>","DOI":"10.3390\/medicina61040689","type":"journal-article","created":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T08:46:20Z","timestamp":1744274780000},"page":"689","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["The Role of Artificial Intelligence in the Diagnosis and Management of Rheumatoid Arthritis"],"prefix":"10.3390","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3996-6546","authenticated-orcid":false,"given":"Adriana Liliana","family":"Vlad","sequence":"first","affiliation":[{"name":"Faculty of Medicine and Pharmacy, \u201cDun\u0103rea de Jos\u201d University of Gala\u021bi, 800008 Gala\u021bi, Romania"},{"name":"\u201cSt. Apostle Andrei\u201d Clinical Emergency County Hospital, 800578 Gala\u021bi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8516-4674","authenticated-orcid":false,"given":"Corina","family":"Popazu","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, \u201cDun\u0103rea de Jos\u201d University of Gala\u021bi, 800008 Gala\u021bi, Romania"},{"name":"\u201cSt. Apostle Andrei\u201d Clinical Emergency County Hospital, 800578 Gala\u021bi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6177-4964","authenticated-orcid":false,"given":"Alina-Maria","family":"Lescai","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, \u201cDun\u0103rea de Jos\u201d University of Gala\u021bi, 800008 Gala\u021bi, Romania"},{"name":"\u201cSt. Apostle Andrei\u201d Clinical Emergency County Hospital, 800578 Gala\u021bi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Doina Carina","family":"Voinescu","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, \u201cDun\u0103rea de Jos\u201d University of Gala\u021bi, 800008 Gala\u021bi, Romania"},{"name":"\u201cSt. Apostle Andrei\u201d Clinical Emergency County Hospital, 800578 Gala\u021bi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexia Anastasia \u0218tefania","family":"Balt\u0103","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, \u201cDun\u0103rea de Jos\u201d University of Gala\u021bi, 800008 Gala\u021bi, Romania"},{"name":"\u201cSt. Apostle Andrei\u201d Clinical Emergency County Hospital, 800578 Gala\u021bi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.cogr.2023.04.001","article-title":"Artificial Intelligence, Machine Learning and Deep Learning in Advanced Robotics, a Review","volume":"3","author":"Soori","year":"2023","journal-title":"Cogn. Robot."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Taye, M.M. (2023). Understanding of Machine Learning with Deep Learning: Architectures, Workflow, Applications and Future Directions. Computers, 12.","DOI":"10.3390\/computers12050091"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Morabito, F.C., Kozma, R., Alippi, C., and Choe, Y. (2024). Advances in AI, Neural Networks, and Brain Computing: An Introduction. Artificial Intelligence in the Age of Neural Networks and Brain Computing, Academic Press.","DOI":"10.1016\/B978-0-323-96104-2.00016-6"},{"key":"ref_4","first-page":"241","article-title":"Artificial Intelligence Revolution in Healthcare: Transforming Diagnosis, Treatment, and Patient Care","volume":"7","author":"Singh","year":"2024","journal-title":"Asian J. Adv. Res."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Asif, S., Wenhui, Y., ur-Rehman, S., ul-Ain, Q., Amjad, K., Yueyang, Y., and Awais, M. (2024). Advancements and Prospects of Machine Learning in Medical Diagnostics: Unveiling the Future of Diagnostic Precision. Arch. Comput. Methods Eng., 1\u201331.","DOI":"10.1007\/s11831-024-10148-w"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Shi, Y., Zhou, M., Chang, C., Jiang, P., Wei, K., Zhao, J., and He, D. (2024). Advancing Precision Rheumatology: Applications of Machine Learning for Rheumatoid Arthritis Management. Front. Immunol., 15.","DOI":"10.3389\/fimmu.2024.1409555"},{"key":"ref_7","first-page":"1","article-title":"Clinical Presentation and Diagnosis of Rheumatoid Arthritis","volume":"13","author":"Trivedi","year":"2024","journal-title":"Ann. Clin. Med. Case Rep."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Imanuel, C.A., Sivatheesan, S., Koyanagi, A., Smith, L., Konrad, M., and Kostev, K. (2023). Associations between Rheumatoid Arthritis and Various Comorbid Conditions in Germany\u2014A Retrospective Cohort Study. J. Clin. Med., 12.","DOI":"10.3390\/jcm12237265"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"201","DOI":"10.4236\/ojra.2024.144022","article-title":"Reconstructive Surgery in Patients with Rheumatoid Arthritis","volume":"14","author":"Manzano","year":"2024","journal-title":"Open J. Rheumatol. Autoimmune Dis."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1093\/jalm\/jfad088","article-title":"Performance of Anti-Carbamylated Protein Antibody Testing in the Routine Evaluation of Rheumatoid Arthritis from a Single Center","volume":"9","author":"Nelson","year":"2024","journal-title":"J. Appl. Lab. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e226","DOI":"10.1016\/S2665-9913(23)00341-7","article-title":"Clinical Consequences of Infliximab Immunogenicity and the Effect of Proactive Therapeutic Drug Monitoring: Exploratory Analyses of the Randomised, Controlled NOR-DRUM Trials","volume":"6","author":"Brun","year":"2024","journal-title":"Lancet Rheumatol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., and Canberk, B. (2024). Machine Learning for Smart Healthcare Management Using IoT. IoT and ML for Information Management: A Smart Healthcare Perspective, Springer Nature Singapore.","DOI":"10.1007\/978-981-97-5624-7_4"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sharma, N., Sapra, R., and Dhaliwal, P. (2024, January 3\u20134). A Comprehensive Review on Knee Osteoarthritis Detection Using Medical Imaging and Machine Learning. Proceedings of the 2024 International Conference on Intelligent Systems for Cybersecurity (ISCS), Gurugram, India.","DOI":"10.1109\/ISCS61804.2024.10581051"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"10921","DOI":"10.1007\/s11042-017-5449-4","article-title":"Automatic Identification of Bone Erosions in Rheumatoid Arthritis from Hand Radiographs Based on Deep Convolutional Neural Network","volume":"77","author":"Murakami","year":"2018","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Saleh, G.A., Batouty, N.M., Haggag, S., Elnakib, A., Khalifa, F., Taher, F., and El-Baz, A. (2022). The Role of Medical Image Modalities and AI in the Early Detection, Diagnosis and Grading of Retinal Diseases: A Survey. Bioengineering, 9.","DOI":"10.3390\/bioengineering9080366"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"152213","DOI":"10.1016\/j.semarthrit.2023.152213","article-title":"Understanding the Role and Adoption of Artificial Intelligence Techniques in Rheumatology Research: An In-Depth Review of the Literature","volume":"61","year":"2023","journal-title":"Semin. Arthritis Rheum."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1038\/s41584-019-0175-0","article-title":"Preventing Psoriatic Arthritis: Focusing on Patients with Psoriasis at Increased Risk of Transition","volume":"15","author":"Scher","year":"2019","journal-title":"Nat. Rev. Rheumatol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1097\/FTD.0000000000001275","article-title":"New Developments and Therapeutic Drug Monitoring Options in Costimulatory Blockade in Solid Organ Transplantation: A Systematic Critical Review","volume":"47","author":"Udomkarnjananun","year":"2025","journal-title":"Ther. Drug Monit."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1038\/s41584-024-01177-7","article-title":"Rheumatology in the Digital Health Era: Status Quo and Quo Vadis?","volume":"20","author":"Knitza","year":"2024","journal-title":"Nat. Rev. Rheumatol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1038\/s41746-024-01013-y","article-title":"Digital Health Technologies and Machine Learning Augment Patient Reported Outcomes to Remotely Characterise Rheumatoid Arthritis","volume":"7","author":"Creagh","year":"2024","journal-title":"npj Digit. Med."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Blasco, J.M., Navarro-Bosch, M., Aroca-Navarro, J.E., Hern\u00e1ndez-Guill\u00e9n, D., Puigcerver-Aranda, P., and Roig-Casas\u00fas, S. (2024). A Virtual Assistant to Guide Early Postoperative Rehabilitation after Reverse Shoulder Arthroplasty: A Pilot Randomized Trial. Bioengineering, 11.","DOI":"10.3390\/bioengineering11020152"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e39972","DOI":"10.2196\/39972","article-title":"Machine Learning Approaches for Predicting Psoriatic Arthritis Risk Using Electronic Medical Records: Population-Based Study","volume":"25","author":"Lee","year":"2023","journal-title":"J. Med. Internet Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"92","DOI":"10.37349\/emd.2024.00038","article-title":"Empowering Rheumatology through Digital Health Technologies: Contributions and Barriers","volume":"2","author":"Benavent","year":"2024","journal-title":"Explor. Musculoskelet. Dis."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Sharma, I., Karwasra, R., Akram, U., Suchal, K., and Singh, S. (2024). AI-Empowered Prediction of Prognosis and Treatment Response in Rheumatoid Arthritis. Artificial Intelligence and Autoimmune Diseases: Applications in the Diagnosis, Prognosis, and Therapeutics, Springer Nature Singapore.","DOI":"10.1007\/978-981-99-9029-0_13"},{"key":"ref_25","first-page":"23","article-title":"Security and Privacy in Digital Healthcare Systems: Challenges and Mitigation Strategies","volume":"42","author":"Jawad","year":"2024","journal-title":"Abhigyan"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rajashekar, N.C., Shin, Y.E., Pu, Y., Chung, S., You, K., Giuffre, M., and Shung, D. (2024, January 11\u201316). Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System. Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA.","DOI":"10.1145\/3613904.3642024"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"69","DOI":"10.2478\/rir-2023-0011","article-title":"A Survey of Artificial Intelligence in Rheumatoid Arthritis","volume":"4","author":"Wang","year":"2023","journal-title":"Rheumatol. Immunol. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"101429","DOI":"10.1016\/j.berh.2019.101429","article-title":"Emerging Role of Ehealth in the Identification of Very Early Inflammatory Rheumatic Diseases","volume":"33","author":"Kataria","year":"2019","journal-title":"Best Pract. Res. Clin. Rheumatol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Khan, F.N., Asim, M., and Qureshi, M.I. (2024). Artificial Intelligence in the Diagnosis and Treatment of Rheumatoid Arthritis: Current Status and Future Prospects. Artificial Intelligence and Autoimmune Diseases: Applications in the Diagnosis, Prognosis, and Therapeutics, Springer Nature Singapore.","DOI":"10.1007\/978-981-99-9029-0_10"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gurke, R., Bendes, A., Bowes, J., Koehm, M., Twyman, R.M., Barton, A., and HIPPOCRATES Consortium (2022). Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis. Biomedicines, 10.","DOI":"10.3390\/biomedicines10102387"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Moe, R.H., and Vliet Vlieland, T.P. (2024). Current and Future Challenges for Rehabilitation for Inflammatory Arthritis. J. Clin. Med., 13.","DOI":"10.3390\/jcm13061808"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1007\/s00296-024-05603-7","article-title":"Nurses\u2019 Roles, Interventions, and Implications for Management of Rheumatic Diseases","volume":"44","author":"Auyezkhankyzy","year":"2024","journal-title":"Rheumatol. Int."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e31043","DOI":"10.2196\/31043","article-title":"Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review","volume":"7","author":"Charow","year":"2021","journal-title":"JMIR Med. Educ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1007\/s00146-020-01125-5","article-title":"The Regulatory Intersections between Artificial Intelligence, Data Protection and Cyber Security: Challenges and Opportunities for the EU Legal Framework","volume":"36","year":"2021","journal-title":"AI Soc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3706","DOI":"10.3390\/nursrep14040271","article-title":"Perceived Worries in the Adoption of Artificial Intelligence among Healthcare Professionals in Saudi Arabia: A Cross-Sectional Survey Study","volume":"14","author":"Alsaedi","year":"2024","journal-title":"Nurs. Rep."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"100470","DOI":"10.1016\/j.puhip.2024.100470","article-title":"Home Living Older Adults\u2019 Subjective Perceptions, Evaluation, and Interpretations of Various Welfare Technology: A Systematic Review of Qualitative Studies","volume":"7","author":"Pajalic","year":"2024","journal-title":"Public Health Pract."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Ezhil Grace, A., and Thandaiah Prabu, R. (2023, January 21\u201323). Advancing Rheumatoid Arthritis Care: Exploring Technological Breakthroughs and Future Directions. Proceedings of the International Conference on Soft Computing: Theories and Applications, Una, India.","DOI":"10.1007\/978-981-97-2031-6_5"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s42358-018-0001-4","article-title":"Fears and Beliefs of People Living with Rheumatoid Arthritis: A Systematic Literature Review","volume":"58","author":"Palominos","year":"2019","journal-title":"Adv. Rheumatol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1007\/s40744-022-00475-4","article-title":"Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review","volume":"9","author":"Momtazmanesh","year":"2022","journal-title":"Rheumatol. Ther."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Inchingolo, F., Inchingolo, A.M., Fatone, M.C., Avantario, P., Del Vecchio, G., Pezzolla, C., and Dipalma, G. (2024). Management of Rheumatoid Arthritis in Primary Care: A Scoping Review. Int. J. Environ. Res. Public Health, 21.","DOI":"10.3390\/ijerph21060662"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Khan, Z., Adil, T., Oduoye, M.O., Khan, B.S., and Ayyazuddin, M. (2024). Assessing the Knowledge, Attitude and Perception of Extended Reality (XR) Technology in Pakistan\u2019s Healthcare Community in an Era of Artificial Intelligence. Front. Med., 11.","DOI":"10.3389\/fmed.2024.1456017"},{"key":"ref_42","first-page":"305","article-title":"Chronic Disease Management through an AI-Powered Application","volume":"17","author":"Arefin","year":"2024","journal-title":"J. Serv. Sci. Manag."},{"key":"ref_43","first-page":"7","article-title":"Revolutionizing Arthritis Care with Artificial Intelligence: A Comprehensive Review of Diagnostic, Prognostic, and Treatment Innovations","volume":"1","author":"Afrazeh","year":"2024","journal-title":"Int. J. Appl. Data Sci. Eng. Health"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1177\/15234223221077304","article-title":"The Impact of Artificial Intelligence on Expertise Development: Implications for HRD","volume":"24","author":"Ardichvili","year":"2022","journal-title":"Adv. Dev. Hum. Resour."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Al-Worafi, Y.M. (2024). Rheumatoid Arthritis Management in Developing Countries. Handbook of Medical and Health Sciences in Developing Countries: Education, Practice, and Research, Springer International Publishing.","DOI":"10.1007\/978-3-030-74786-2_35-1"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e40973","DOI":"10.2196\/40973","article-title":"Preparing for an Artificial Intelligence\u2013Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings","volume":"2","author":"Jeyakumar","year":"2023","journal-title":"JMIR AI"},{"key":"ref_47","first-page":"55","article-title":"The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy in Clinical Medicine","volume":"1","author":"Qamar","year":"2024","journal-title":"Multidiscip. J. Healthc."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"127","DOI":"10.3322\/caac.21552","article-title":"Artificial Intelligence in Cancer Imaging: Clinical Challenges and Applications","volume":"69","author":"Bi","year":"2019","journal-title":"CA Cancer J. Clin."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"22","DOI":"10.22215\/timreview\/1111","article-title":"Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector","volume":"7","author":"Engelhardt","year":"2017","journal-title":"Technol. Innov. Manag. Rev."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Mansour, R., Abdel-Razeq, H., Al-Hussaini, M., Shamieh, O., Al-Ibraheem, A., Al-Omari, A., and Mansour, A.H. (2024). Systemic Barriers to Optimal Cancer Care in Resource-Limited Countries: Jordanian Healthcare as an Example. Cancers, 16.","DOI":"10.3390\/cancers16061117"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"102494","DOI":"10.1016\/j.ijinfomgt.2022.102494","article-title":"Algorithm Awareness: Why User Awareness Is Critical for Personal Privacy in the Adoption of Algorithmic Platforms?","volume":"65","author":"Shin","year":"2022","journal-title":"Int. J. Inf. Manag."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"9907","DOI":"10.1007\/s10639-023-12172-y","article-title":"Investigation into the Influence of Socio-Cultural Factors on Attitudes toward Artificial Intelligence","volume":"29","author":"Kim","year":"2024","journal-title":"Educ. Inf. Technol."}],"container-title":["Medicina"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1648-9144\/61\/4\/689\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:13:13Z","timestamp":1760029993000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1648-9144\/61\/4\/689"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,9]]},"references-count":52,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["medicina61040689"],"URL":"https:\/\/doi.org\/10.3390\/medicina61040689","relation":{},"ISSN":["1648-9144"],"issn-type":[{"value":"1648-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,9]]}}}