Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on clinicopathological features offer limited predictive accuracy and lack ...

To prevent data imbalance, a common problem in environmental modeling where non-flooded areas vastly outnumber flooded points ...

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...

Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...

Skin cancer impacts millions of Americans annually, but your chances of getting skin cancer and when it is diagnosed depend ...

Ex vivo lung perfusion (EVLP) provides a platform for testing therapies but faces challenges in standardizing drug evaluation. At AAPS PharmSci 360, Xuanzi Zhou says digital twins accurately predict ...

Researchers sought to develop and validate artificial neural networks for overall survival and progression-free survival in older adults with HNSCC following definitive chemoradiation.

Researchers at the University of California San Diego School of Medicine have developed a new approach for identifying ...

In analyzing dozens of AI PoCs that sailed on through to full production use — or didn’t — six common pitfalls emerge.

The newest research from Southeast Asia shows AI models can predict dengue outbreaks two to four weeks in advance. In some ...

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.

Huma Abia Kanta, a 16-year-old from Guwahati, presented her AI research on predicting pigment purity at an international ...