Artificial intelligence (AI) tools can help physicians predict treatment and survival outcomes in patients with advanced non-small cell lung cancer (NSCLC) treated with immunotherapy, according to a new study published in Nature Medicine. The study reported findings from the I3LUNG project, a large, international trial aimed at improving the current treatment of metastatic NSCLC by developing AI-based predictive models that can help determine the best therapeutic approach for each individual.

Contrary to some predictions, the use of artificial intelligence (AI) agents could lead to more, not fewer, health care professionals working in the United States, according to a new article by a physician and health policy researcher at Weill Cornell Medicine who surveyed economic theory and the history of technology in health care.

The rapid adoption and growing sophistication of medical AI tools have led to concerns that AI could

Cancer immunotherapy has transformed the treatment landscape for many malignancies by activating or restoring antitumor immune responses. Some patients achieve deep and durable remission, but many show primary resistance, experience disease progression after an initial response, or develop immune-related adverse events. Complex response patterns, including pseudoprogression and hyperprogression, further complicate treatment evaluation and adjustment.

New research shows how artificial intelligence, combined with advanced experimental science, can help find “hidden” and unexplored proteins in the human body and reveal what they actually do, according to a new study published in Nature.

The discovery suggests a new way to study how cells communicate, survive stress and possibly support disease.

Mayo Clinic researchers have found that artificial intelligence (AI)-enabled spatial analysis can identify patterns in routine pathology slides that may help clinicians identify which patients with pancreatic cancer are at greater risk of recurrence after treatment and surgery.

The study, published in Clinical Cancer Research, suggests that looking at how residual cancer is

An artificial intelligence (AI) model that analyzes women’s past and recent annual 3D mammograms is more effective at predicting five-year risk of developing breast cancer than a tool that uses only the most recent, single 3D mammogram, as well as an AI model that analyzes 2D mammograms, a new study shows.

Artificial intelligence (AI) holds profound potential to reshape public health. Although its application accelerates threat detection and targeted interventions, the rapid deployment has outpaced the regulatory, validation, and equity safeguards standard to traditional health interventions.

In a recent analytic essay, Dr. Terry Adirim from the Department of Pediatrics and the Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, and