Researchers at MUSC Hollings Cancer Center have developed a machine learning tool to identify cancer patients who may be at high risk for financial toxicity – the financial stress and hardship that ...

A new research published in the Journal of the American Medical Association revealed that a machine learning model which ...

A new machine-learning approach for prostate-specific membrane antigen (PSMA) treatment of metastatic castration-resistant prostate cancer (mCRPC) could estimate radiation dose to tumors and healthy ...

Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

Millions of people are diagnosed with Alzheimer's disease each year, comprising 60% to 70% of dementia cases worldwide. While cognitive impairment and structural brain changes are indicative of ...

Using a form of machine learning called self-supervised learning, Mass General Brigham researchers have created a new predictive artificial intelligence model, which they say could help generate ...

illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...

A machine learning model uses cloud type and cloud cover to predict rapid changes in surface solar irradiance, including short-term “ramp” events that affect grid stability. When tested across 15 ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Investopedia / Zoe Hansen Overfitting occurs when a model is too closely ...