Doctors around the world may soon have access to a new tool that could better predict whether individual cancer patients will benefit from immune checkpoint inhibitors - a type of immunotherapy - using only routine blood tests and clinical data.

The artificial intelligence–based model, dubbed SCORPIO, was developed by a team of researchers from Memorial Sloan Kettering Cancer Center (MSK) and the Tisch Cancer Institute at Mount Sinai.

Introducing Annotatability - a powerful new framework to address a major challenge in biological research by examining how artificial neural networks learn to label genomic data. Genomic datasets often contain vast amounts of annotated samples, but many of these samples are annotated either incorrectly or ambiguously.

A new study from Vanderbilt University Medical Center shows that clinical alerts driven by artificial intelligence (AI) can help doctors identify patients at risk for suicide, potentially improving prevention efforts in routine medical settings.

A new international study led by researchers at Karolinska Institutet in Sweden shows that AI-based models can outperform human experts at identifying ovarian cancer in ultrasound images. The study is published in Nature Medicine.

Patients with opioid use disorder can reduce their days of opioid use and stay in treatment longer when using a smartphone app as supportive therapy in combination with medication, a new study by The University of Texas Health Science Center at San Antonio (UT Health San Antonio) shows.

Pioneering research has unveiled a powerful new tool in the fight against skin cancer, combining cutting-edge artificial intelligence (AI) with deep learning to enhance the precision of skin lesion classification. This innovative approach, which utilizes a weighted ensemble of transfer learning models and test time augmentation (TTA), promises to significantly improve the accuracy of skin cancer diagnosis.

Physical examinations are important diagnostic tools that can reveal critical insights into a patient's health, but complex conditions may be overlooked if a clinician lacks specialized training in that area. While previous research has investigated using large language models (LLMs) as tools to aid in providing diagnoses, their use in physical exams remains untapped.