Artificial Intelligence in Medical Recommendation Systems: A Literature Review
DOI:
https://doi.org/10.32870/recibe.v12i2.311Keywords:
eHealth, Recomender Systems, Artificial Intelligence, Software, Systematic Literature ReviewAbstract
In Mexico, approximately one in three people search for information about medical care through the Internet, considering factors such as specialty, hours, location, cost, treatment effectiveness, and quality of medical treatment. In order to address these searches, recommender systems have been developed that offer personalized suggestions based on explicit and implicit user information. These systems use various data sources, including the Internet of Things, to balance accuracy, added value, dispersion, and stability in recommendations. Despite the wide application in eHealth, current research needs a specific focus on physician recommendation systems. This study aims to present the most recent works in this area, analyzing approaches, methods, techniques, and trends through a systematic literature review following the evidence-based software engineering (EBSE) process. The results show more recommendation techniques based on machine learning, heuristic logic, and a combination of both approaches (hybrids). Finally, open research areas and trends in this field are identified, which will be of interest for future applications in the medical field.References
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