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MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation and degradation of mRNA and have been associated with many diseases. Artificial Intelligence (AI) is an evolving cluster of interrelated fields, with machine learning (ML) standing out as one of the most prominent AI fields, with a plethora of applications in almost every aspect of human life. ML could be defined as computer algorithms that learn from past data to predict future data. This review comprehensively reviews the current applications of microRNA-based ML models in healthcare. The majority of the identified studies investigated the role of microRNA-based ML models in the management of cancer and specifically gastric cancer (maximum diagnostic accuracy (Accmax): 94%), pancreatic cancer (Accmax: 93%), colorectal cancer (Accmax: 100%), breast cancer (Accmax: 97%), ovarian cancer, neck squamous cell carcinoma, liver cancer, lung cancer (Accmax: 100%), and melanoma. Except for cancer, microRNA-based ML models have been applied for a plethora of other diseases, including ulcerative colitis (Accmax: 92.8%), endometriosis, gestational diabetes mellitus (Accmax: 86%), hearing loss, ischemic stroke, coronary heart disease (Accmax: 96%), tuberculosis, pulmonary arterial hypertension (Accmax: 83%), dementia (Accmax: 82.9%), major cardiovascular events in end-stage renal disease patients, and alcohol dependence (Accmax: 79.1%). Our findings suggest that the development of microRNA-based ML models could be used to enhance the diagnostic accuracy of a plethora of diseases while at the same time substituting or minimizing the use of more invasive diagnostic means (such as endoscopy). Even not as fast as anticipated, AI will eventually infiltrate the entire healthcare industry. AI is the key to a clinical practice where medicine's inherent complexity is embraced. Therefore, AI will become a reality that physicians should conform with to avoid becoming obsolete., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Introduction: Ischemia-Reperfusion (I/R) injuries are caused by complex interrelated mechanisms and pathways. Regarding the liver, I/R injuries and their clinical manifestations are crucial for the surgical outcome. Despite its importance, there is no broadly accepted therapy either for the prevention or for the management of I/R injury. I/R injury of the liver can occur either during hepatic surgery (warm) or during the transplantation procedure (cold). MicroRNAs play a pivotal role in the mechanism of I/R injury, as they regulate the expression of the cellular participants and humoral factors associated with I/R injury., Objective: In this review, we highlight the microRNAs that are involved in the I/R injury of the liver, and the molecular pathways that they regulate. In addition, we discuss the potential role of circulating microRNAs as biomarkers and their role as pharmacological targets in the prevention, diagnosis and treatment of I/R injuries., Method: We conducted a comprehensive review of the PubMed bibliographic database regarding microRNAs and I/R injuries of the liver., Results: In diagnostics, microRNA panels could replace invasive diagnostic procedures, relieving patients of the associated complications. In therapeutics, microRNAs, agomirs, antagomirs and other drugs can be used to shift the balance between proapoptotic and survival pathways, to alleviate the liver damage caused by I/R. In transplantation procedures, microRNA profiling could decrease the incidence of early graft dysfunction, especially regarding marginal grafts., Conclusion: Although microRNAs seem a very promising clinical tool in the management of I/R injuries, further research is required, until microRNAs become a novel tool in the diagnosis and monitoring of an I/R injury of the liver., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)