Machine learning for prediction of cutaneous adverse events in patients receiving anti-PD-1 immunotherapy

J Am Acad Dermatol. 2021 Jan;84(1):183-185. doi: 10.1016/j.jaad.2020.04.069. Epub 2020 Apr 22.

Authors

Ryan T Lewinson¹, Daniel E Meyers², Isabelle A Vallerand³, Aleksi Suo², Michelle L Dean², Tina Cheng², D Gwyn Bebb², Don G Morris⁴

Affiliations

¹ Division of Dermatology, University of Calgary, Ontario, Canada; Faculty of Kinesiology, University of Calgary, Ontario, Canada.
² Department of Oncology, University of Calgary, Ontario, Canada.
³ Division of Dermatology, University of Calgary, Ontario, Canada.
⁴ Department of Oncology, University of Calgary, Ontario, Canada. Electronic address: don.morris@ahs.ca.

PMID: 32334053
DOI: 10.1016/j.jaad.2020.04.069

No abstract available

Publication types

Letter

MeSH terms

Carcinoma, Non-Small-Cell Lung / drug therapy*
Drug Eruptions / etiology*
Humans
Immune Checkpoint Inhibitors / adverse effects*
Lung Neoplasms / drug therapy*
Machine Learning
Melanoma / drug therapy*
Melanoma / secondary
Neural Networks, Computer
Predictive Value of Tests
Proof of Concept Study
ROC Curve
Risk Assessment / methods
Skin Neoplasms / drug therapy*
Skin Neoplasms / pathology

Substances

Immune Checkpoint Inhibitors