Title
Machine learning in medical applications: A review of state-of-the-art methods
Abstract
Applications of machine learning (ML) methods have been used extensively to solve various complex challenges in recent years in various application areas, such as medical, financial, environmental, marketing, security, and industrial applications. ML methods are characterized by their ability to examine many data and discover exciting relationships, provide interpretation, and identify patterns. ML can help enhance the reliability, performance, predictability, and accuracy of diagnostic systems for many diseases. This survey provides a comprehensive review of the use of ML in the medical field highlighting standard technologies and how they affect medical diagnosis. Five major medical applications are deeply discussed, focusing on adapting the ML models to solve the problems in cancer, medical chemistry, brain, medical imaging, and wearable sensors. Finally, this survey provides valuable references and guidance for researchers, practitioners, and decision-makers framing future research and development directions.
Year
DOI
Venue
2022
10.1016/j.compbiomed.2022.105458
COMPUTERS IN BIOLOGY AND MEDICINE
Keywords
DocType
Volume
Machine learning, Medical field, Diagnosis, Healthcare, Medical applications
Journal
145
ISSN
Citations 
PageRank 
0010-4825
2
0.37
References 
Authors
111
7
Search Limit
100111