The next major advance in medical AI may lie not in analyzing more data, but in understanding how health data change over time. A recent editorial in Intelligent Medicine argues that dynamics-driven ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...

In A Nutshell AI tools that track how the body’s molecular networks change over time may detect diseases like cancer, ...

Head and neck cancers represent a biologically heterogeneous group of malignancies requiring accurate diagnosis, staging, and risk stratification for ...

Alumna, author and machine learning expert Vivienne Ming explains why the best defense against AI’s downsides is investing in human skills — and using the technology inquisitively, not passively ...

From Watson's $15B Jeopardy-to-medicine failure to 800+ FDA-cleared AI tools: the complete history of AI in healthcare.

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

A new study using an advanced "digital twin" artificial intelligence model has found that factors such as loneliness, ...

Drug resistance remains a central barrier to durable responses across cancer therapies, spanning targeted agents, cytotoxic chemotherapy, endocrine ...

The global rise in the prevalence of obesity highlights the need for accessible and effective solutions for obesity ...

Based on this, this study retrospectively analyzes the clinical testing data of patients with diabetic nephropathy and those with simple diabetes mellitus to investigate the predictive value of ...