ADOPTION OF MACHINE LEARNING IN DIAGNOSIS AND TREATMENT IN HEALTHCARE; A SYSTEMATIC LITERATURE REVIEW
ADOPTION OF MACHINE LEARNING IN DIAGNOSIS AND TREATMENT IN HEALTHCARE; A SYSTEMATIC LITERATURE REVIEW
Njama Caroline Diana - iAfricaCoop NPC
ABSTRACT
The utilization of machine learning (ML) has the capacity to greatly influence the examination of intricate data sources within the field of medical practice. Machine learning algorithms are presently utilized in the medical domain to identify patterns and make predictions concerning possible outcomes. The healthcare sector has made notable advancements in utilizing machine learning (ML) technology, particularly in areas such as diagnosis, predicting clinical events, and forecasting mortality trends. We employed a methodical approach to locate and examine scholarly articles that were published between the years 2015 and 2022. A total of 26 articles were identified and reviewed. The findings suggest that machine learning has the capability to improve the accessibility and efficiency of service provision. Despite the considerable potential of machine learning in the healthcare industry, there has been a surprising lack of research in this area. The study indicates that most research in this area has primarily focused on subjects such as diagnosing and predicting risks, suggesting treatments, and creating medications.
