학술논문
Guest Editorial Advanced Machine Learning and Artificial Intelligence Tools for Computational Biology: Methodologies and Challenges
Document Type
Periodical
Author
Source
IEEE Journal of Biomedical and Health Informatics IEEE J. Biomed. Health Inform. Biomedical and Health Informatics, IEEE Journal of. 28(4):1883-1885 Apr, 2024
Subject
Language
ISSN
2168-2194
2168-2208
2168-2208
Abstract
In recent years, the management and analysis of biological data have experienced exponential growth propelled by the relentless advancement of machine learning (ML) and artificial intelligence (AI) technologies. This is driven mainly by the remarkable ability and potentials of AI-based systems to craft sophisticated, yet effective, algorithms and analytical models tailored for the interpretation of biological information; thus, assist in making accurate predictions and/or decisions [1]. The surge in AI adoption is not unfounded; it's a response to the overwhelming increase in both the volume and acquisition rates of biological data.