Accessibility settings

This paper is in the following e-collection/theme issue:

Cancer Prognosis Models and Machine Learning (133) Cancer Survivorship (443) Machine Learning (3029) Artificial Intelligence (4518) Precision Medicine (420) Cancer genomic data analysis (18)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74196, first published .
Doctor interacting with futuristic medical icons on a blue background.

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset

Authors of this article:

Polycarp Nalela1 Author Orcid Image ;   Deepthi Rao1 Author Orcid Image ;   Praveen Rao1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Khodeer D, Ukozehasi C, Alaseem A, Abdelmonem S. Applications of artificial intelligence and machine learning models in the prognosis and diagnosis of ovarian cancer. Frontiers in Oncology 2026;16 View

Conference Proceedings

  1. K R, Kumari V, R V, Pillai N, Sivakumar P, S R. 2026 6th International Conference on Expert Clouds and Applications (ICOECA). Detection of Kidney Tumor Cancer Stages using Explainable Artificial Intelligence View