Supervised learning applied to classifying fallers versus non-fallers among older adults with cancer.

ABSTRACT:

Introduction

Supervised machine learning approaches are increasingly used to analyze clinical data, including in geriatric oncology. This study presents a machine learning approach to understand falls in a cohort of older adults with advanced cancer starting chemotherapy, including fall prediction and identification of contributing factors.

Materials and methods

This secondary analysis of prospectively collected data from the GAP 70+ Trial (NCT02054741; PI: Mohile) enrolled patients aged ≥70 with advanced cancer and ≥ 1 geriatric assessment domain impairment who planned to start a new cancer treatment regimen. Of ≥2000 baseline variables ("features") collected, 73 were selected based on clinical judgment. Machine learning models to predict falls at three months were develope

SUBMITTER: Ramsdale E 

PROVIDER: S-EPMC10174263 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature