Semantic Scholar Open Access 2018 734 sitasi

eDoctor: machine learning and the future of medicine

G. Handelman H. Kok R. Chandra A. H. Razavi M. Lee +1 lainnya

Abstrak

Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer‐aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML, explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.

Topik & Kata Kunci

Penulis (6)

G

G. Handelman

H

H. Kok

R

R. Chandra

A

A. H. Razavi

M

M. Lee

H

H. Asadi

Format Sitasi

Handelman, G., Kok, H., Chandra, R., Razavi, A.H., Lee, M., Asadi, H. (2018). eDoctor: machine learning and the future of medicine. https://doi.org/10.1111/joim.12822

Akses Cepat

Lihat di Sumber doi.org/10.1111/joim.12822
Informasi Jurnal
Tahun Terbit
2018
Bahasa
en
Total Sitasi
734×
Sumber Database
Semantic Scholar
DOI
10.1111/joim.12822
Akses
Open Access ✓