Cargando…
Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
IMPORTANCE: Machine learning algorithms could identify patients with cancer who are at risk of short-term mortality. However, it is unclear how different machine learning algorithms compare and whether they could prompt clinicians to have timely conversations about treatment and end-of-life preferen...
Autores principales: | Parikh, Ravi B., Manz, Christopher, Chivers, Corey, Regli, Susan Harkness, Braun, Jennifer, Draugelis, Michael E., Schuchter, Lynn M., Shulman, Lawrence N., Navathe, Amol S., Patel, Mitesh S., O’Connor, Nina R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822091/ https://www.ncbi.nlm.nih.gov/pubmed/31651973 http://dx.doi.org/10.1001/jamanetworkopen.2019.15997 |
Ejemplares similares
-
Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial
por: Manz, Christopher R., et al.
Publicado: (2020) -
Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial
por: Li, Eric, et al.
Publicado: (2022) -
Long-term Effect of Machine Learning–Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer: A Randomized Clinical Trial
por: Manz, Christopher R., et al.
Publicado: (2023) -
Performance Drift in a Mortality Prediction Algorithm during the SARS-CoV-2 Pandemic
por: Parikh, Ravi B., et al.
Publicado: (2022) -
Evaluation of Spending Differences Between Beneficiaries in Medicare Advantage and the Medicare Shared Savings Program
por: Parikh, Ravi B., et al.
Publicado: (2022)