Work

Assessment of supervised machine learning methods for predicting COVID-19 likelihood

Year: 2025

Type: conference-paper

Source: IEEE Middle East and North Africa Communications Conference (MENACOMM)

DOI: 10.1109/menacomm62946.2025.10911021

Authors: Abbas Rammal, Rabih Assaf, Mohammad Kacim

Institutions: Lebanese American University, Holy Spirit University of Kaslik

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4408402304

FWCI: 5.669

Cites: 22

Cited by: 1

Related to: 10