A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

Data was split into training (80%) and testing (20%) sets. For the prediction task, we applied GPT-4o and compared with XGBoost, one of the strongest non-generative machine learning models. We used ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Alternative lending is a vital source of credit for consumers underserved by traditional banks. This study examines how integrating additional data and advanced machine learning enhances default ...

We used supervised machine learning approaches across 3 predictive tasks (Figure 1). Model features (chronic conditions) were determined using a priori clinical knowledge and preprocessed differently ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

New research presented during the 2024 San Antonio Breast Cancer Symposium (SABCS) reveals a new machine learning model that could change the way metastatic breast cancer is treated in the future. By ...