A recommendation system is a system that, based on a limited amount of information provided by users as well as the feedback given to goods, persons, and locations by other users, provides appropriate suggestions to the user. Today, with the large number of physicians and specialists, it seems necessary to have a system for identifying the right specialist and experienced physician for the patient. We present in this study a system for medical recommendations that analyzes physicians and specialists. It uses collaborative filtering and scores provided by other users to suggest physician recommendations according to the area of expertise of the physician. Research conducted and evaluation of results show that this system can successfully recommend a specialist doctor to the user in 90% of cases.
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Reza Molaee Fard received his MSc degree in 2020 from Islamic Azad University, Dezful Branch. His research interests include data mining, Recommender systems, and wireless sensor networks, and he has conducted research in these areas.
Payam Yarahmadi received his M.SC in 2009 from Taras University of Ukraine and received his P.HD in 2015 from Taras University of Ukraine. His favorite research field is data mining, web mining and machine learning.
Molaee Fard, R., & Yarahmadi, P. (2022). A Recommendation System in the Medical Industry using SW-DBSCAN Algorithm. International Journal of Web Research, 5(1), 82-87. doi: 10.22133/ijwr.2023.357731.1131
MLA
Reza Molaee Fard; Payam Yarahmadi. "A Recommendation System in the Medical Industry using SW-DBSCAN Algorithm". International Journal of Web Research, 5, 1, 2022, 82-87. doi: 10.22133/ijwr.2023.357731.1131
HARVARD
Molaee Fard, R., Yarahmadi, P. (2022). 'A Recommendation System in the Medical Industry using SW-DBSCAN Algorithm', International Journal of Web Research, 5(1), pp. 82-87. doi: 10.22133/ijwr.2023.357731.1131
VANCOUVER
Molaee Fard, R., Yarahmadi, P. A Recommendation System in the Medical Industry using SW-DBSCAN Algorithm. International Journal of Web Research, 2022; 5(1): 82-87. doi: 10.22133/ijwr.2023.357731.1131
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