Review Of Algorithms, Methods And Applications Of Machine Learning In The Field Of Medicine

Inspired by pattern theory and computational learning theory, machine learning examines the study and construction of algorithms that can learn and make predictions based on data. Such algorithms do not simply follow the program's commands and make predictions or decisions through modeling of sample input data. Machine learning is used in computing tasks where it is difficult or impossible to design and program explicit algorithms with proper performance; Some applications include email filtering, identification of Internet intruders or internal malwares that intend to create an information breach, optical text reader, ranking learning, and machine vision. Considering the sensitivity of the medical field, therefore, machine learning is used to increase the ability in this field and to feel the need in this industry. With the generation of large amounts of medical data, there is an urgent need to effectively utilize this data to benefit medical and healthcare sectors worldwide. This technique helps clinicians analyze data to identify patterns and warning signs, resulting in improved patient care quality, cost-effectiveness, and reduced readmission and mortality rates. Several machine learning techniques are used to diagnose and predict diseases in medical sciences. This article is a review article that, using the review of recent studies, has a glimpse of the application of machine learning and its techniques in clinical and medical care and discusses its potential role

کلیدواژه ها:

Medical science ، machine learning ، artificial intelligence ، algorithm ، epidemic ، medical images.