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

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

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

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

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...

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

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

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 ...

Huma Abia Kanta, a 16-year-old from Guwahati, presented her AI research on predicting pigment purity at an international conference. Her successful model will be published, and she has also ...

Researchers at the University of California San Diego School of Medicine have developed a new approach for identifying individuals with skin cancer that combines genetic ancestry, lifestyle and social ...

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

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