Precision Medicine in Oncology - Machine Learning Recommendations
Overview
Overview
Authors
Authors
Affiliations
Affiliations
Soon will be listed here.
Abstract
The article describes recommendations related to machine learning methods in oncology.
Citing Articles
Zhang R, Yang Z, Shen X, Xia L, Cheng Y J Multidiscip Healthc. 2024; 17:1743-1754.
PMID: 38680878 PMC: 11055519. DOI: 10.2147/JMDH.S455669.
References
1.
Blease C, Kharko A, Bernstein M, Bradley C, Houston M, Walsh I
. Machine learning in medical education: a survey of the experiences and opinions of medical students in Ireland. BMJ Health Care Inform. 2022; 29(1).
PMC: 8808371.
DOI: 10.1136/bmjhci-2021-100480.
View
2.
Zhang B, Ao B, Lu X, Yang S, Bao P, Wang H
. Global research trends on precision oncology: A systematic review, bibliometrics, and visualized study. Medicine (Baltimore). 2022; 101(43):e31380.
PMC: 9622693.
DOI: 10.1097/MD.0000000000031380.
View
3.
Richter T, Fishbain B, Markus A, Richter-Levin G, Okon-Singer H
. Using machine learning-based analysis for behavioral differentiation between anxiety and depression. Sci Rep. 2020; 10(1):16381.
PMC: 7532220.
DOI: 10.1038/s41598-020-72289-9.
View
4.
Hummel M, Edelmann D, Kopp-Schneider A
. Clustering of samples and variables with mixed-type data. PLoS One. 2017; 12(11):e0188274.
PMC: 5705083.
DOI: 10.1371/journal.pone.0188274.
View
5.
Ordak M
. COVID-19 research: quality of biostatistics. Arch Med Sci. 2022; 18(1):257-259.
PMC: 8826691.
DOI: 10.5114/aoms/144644.
View