Cargando…
Validating a Machine Learning Algorithm to Predict 30-Day Re-Admissions in Patients With Heart Failure: Protocol for a Prospective Cohort Study
BACKGROUND: Big data solutions, particularly machine learning predictive algorithms, have demonstrated the ability to unlock value from data in real time in many settings outside of health care. Rapid growth in electronic medical record adoption and the shift from a volume-based to a value-based rei...
Autores principales: | Kakarmath, Sujay, Golas, Sara, Felsted, Jennifer, Kvedar, Joseph, Jethwani, Kamal, Agboola, Stephen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231891/ https://www.ncbi.nlm.nih.gov/pubmed/30181113 http://dx.doi.org/10.2196/resprot.9466 |
Ejemplares similares
-
A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data
por: Golas, Sara Bersche, et al.
Publicado: (2018) -
Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study
por: op den Buijs, Jorn, et al.
Publicado: (2018) -
Assessing the Usability of an Automated Continuous Temperature Monitoring Device (iThermonitor) in Pediatric Patients: Non-Randomized Pilot Study
por: Kakarmath, Sujay S, et al.
Publicado: (2018) -
A Multimodal mHealth Intervention (FeatForward) to Improve Physical Activity Behavior in Patients with High Cardiometabolic Risk Factors: Rationale and Protocol for a Randomized Controlled Trial
por: Agboola, Stephen, et al.
Publicado: (2016) -
Improving Outcomes in Cancer Patients on Oral Anti-Cancer Medications Using a Novel Mobile Phone-Based Intervention: Study Design of a Randomized Controlled Trial
por: Agboola, Stephen, et al.
Publicado: (2014)