Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
ascopubs.org

Regression Derived Staging Model to Predict Overall and Disease Specific Survival in Patients With Major Salivary Gland Carcinomas With Independent External Validation

The current American Joint Cancer Committee (AJCC) staging system for salivary gland tumors does not include histology and grade in its classification despite their proven prognostic importance. We ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
The American Journal of Managed Care

Development and Validation of a Medication Intensity Scale Derived From Computerized Pharmacy Data That Predicts Emergency Hospital Utilization for Persistent Asthma

Methods: The development sample consisted of 1079 HMO members aged 18 to 56 years with persistent asthma. The scale used medication cut-points as predictors for next-year emergency hospital ...
ascopubs.org

Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

Indication-Specific Generic Uptake of Imatinib Demonstrates the Impact of Skinny Labeling Participants with stage I-III breast cancer were prospectively included from CANTO (ClinicalTrials.gov ...