European Medical Journal

AI Model Predicts Cardiac Tamponade During Ablation

A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...
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 ...
ascopubs.org

Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
University of Birmingham

Machine‑learning framework could transform prediction of drug side effects

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Risk.net

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...