A drug recommender system Based on Collaborative Filtering for Covid-19 patients
28th International Computer Conference, Computer Society of Iran, CSICC 2023
; 2023.
Article
Dans Anglais
| Scopus | ID: covidwho-2324999
ABSTRACT
The epidemic caused by a new mutation of the coronavirus family called Covid-19 has created a global crisis involving all the world's countries. This disease has become a severe danger to everyone due to its unknown nature, high spread, and inability to detect the infected. In this regard, one of the important issues facing patients with Covid-19 is the prescription of Drugs according to the severity of the disease and considering the records of underlying diseases in people. In recent years, recommender systems have been developed significantly along with the advancement in information technology and artificial intelligence, which is one of its applications in various fields of medical sciences. Among them, we can refer to recommending systems for the prevention, control, and treatment of diseases. In this research, using the collaborative filtering approach as one of the types of recommender systems as well as the K-means clustering algorithm, a Drug recommendation system for patients with Covid-19 in the treatment stage of the disease is presented. The results of this research show that this recommender system has an acceptable performance based on the evaluation criteria of precision, recall, and F1-score compared to the opinions of experts in this field. © 2023 IEEE.
collaborative filtering; Covid-19; recommender system; Disease control; Diseases; K-means clustering; Medical information systems; Patient treatment; Acceptable performance; Coronaviruses; Evaluation criteria; F1 scores; ITS applications; K-means clustering algorithms; Medical science; Performance based; Recommender systems
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
Scopus
Type d'étude:
Études expérimentales
/
Étude pronostique
langue:
Anglais
Revue:
28th International Computer Conference, Computer Society of Iran, CSICC 2023
Année:
2023
Type de document:
Article
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