Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Assessment of Circulating Tumor DNA Burden in Patients With Metastatic Gastric Cancer Using Real-World Data Endometrial cancer (EC) is the most common gynecologic cancer in the United States with ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...