{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T01:00:42Z","timestamp":1792890042576,"version":"4.5.0"},"reference-count":55,"publisher":"Bentham Science Publishers Ltd.","issue":"3","content-domain":{"domain":["eurekaselect.com"],"crossmark-restriction":true},"short-container-title":["MIRNA"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:sec>\n                    <jats:title>:<\/jats:title>\n                    <jats:p>MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the\ntranslation and degradation of mRNA and have been associated with many diseases. Artificial Intelligence\n(AI) is an evolving cluster of interrelated fields, with machine learning (ML) standing out as\none of the most prominent AI fields, with a plethora of applications in almost every aspect of human\nlife. ML could be defined as computer algorithms that learn from past data to predict future data. This\nreview comprehensively reviews the current applications of microRNA-based ML models in\nhealthcare. The majority of the identified studies investigated the role of microRNA-based ML models\nin the management of cancer and specifically gastric cancer (maximum diagnostic accuracy (Accmax):\n94%), pancreatic cancer (Accmax: 93%), colorectal cancer (Accmax: 100%), breast cancer\n(Accmax: 97%), ovarian cancer, neck squamous cell carcinoma, liver cancer, lung cancer (Accmax:\n100%), and melanoma. Except for cancer, microRNA-based ML models have been applied for a\nplethora of other diseases, including ulcerative colitis (Accmax: 92.8%), endometriosis, gestational\ndiabetes mellitus (Accmax: 86%), hearing loss, ischemic stroke, coronary heart disease (Accmax:\n96%), tuberculosis, pulmonary arterial hypertension (Accmax: 83%), dementia (Accmax: 82.9%),\nmajor cardiovascular events in end-stage renal disease patients, and alcohol dependence (Accmax:\n79.1%). Our findings suggest that the development of microRNA-based ML models could be used to\nenhance the diagnostic accuracy of a plethora of diseases while at the same time substituting or minimizing\nthe use of more invasive diagnostic means (such as endoscopy). Even not as fast as anticipated,\nAI will eventually infiltrate the entire healthcare industry. AI is the key to a clinical practice\nwhere medicine's inherent complexity is embraced. Therefore, AI will become a reality that physicians\nshould conform with to avoid becoming obsolete.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2174\/2211536611666220818145553","type":"journal-article","created":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T08:01:51Z","timestamp":1660896111000},"page":"175-184","update-policy":"https:\/\/doi.org\/10.2174\/bsp_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["The Use of Machine Learning in MicroRNA Diagnostics: Current\nPerspectives"],"prefix":"10.2174","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5417-8686","authenticated-orcid":true,"given":"Chrysanthos D.","family":"Christou","sequence":"first","affiliation":[{"name":"Department of Transplantation Surgery, Hippokration General Hospital, School of Medicine, Aristotle University of\nThessaloniki, Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6755-8218","authenticated-orcid":true,"given":"Angelos C.","family":"Mitsas","sequence":"additional","affiliation":[{"name":"School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ioannis","family":"Vlachavas","sequence":"additional","affiliation":[{"name":"Intelligent Systems Laboratory, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georgios","family":"Tsoulfas","sequence":"additional","affiliation":[{"name":"Department of Transplantation Surgery, Hippokration General Hospital, School of Medicine, Aristotle University of\nThessaloniki, Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"965","reference":[{"key":"ref=1","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1146\/annurev.cellbio.23.090506.123406","volume":"23","author":"Bushati N.","year":"2007","unstructured":"Bushati N.; Cohen S.M.; MicroRNA functions. 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