Research

Deep Learning can Predict Lung Cancer Risk from Single LDCT Scan

A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT scan, according to new research published at the ATS 2025 International Conference.

The model, called Sybil, which was originally developed using National Lung Screening Trial (NLST) data by investigators from the Massachusetts Institute of Technology and Harvard Medical School, could be used to guide more personalized lung cancer screening strategies.

Generative AI on Track to Shape the Future of Drug Design

Using advanced artificial intelligence (AI), researchers have developed a novel method to make drug development faster and more efficient.

In a new paper, Xia Ning, lead author of the study and a professor of biomedical informatics and computer science and engineering at The Ohio State University, introduces DiffSMol, a generative AI model capable of generating realistic 3D structures of small molecules that can serve as promising drug candidates.

AI Tool Uses Face Photos to Estimate Biological Age and Predict Cancer Outcomes

Eyes may be the window to the soul, but a person's biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm called FaceAge that uses a photo of a person’s face to predict biological age and survival outcomes for patients with cancer.

AI Model Improves Delirium Prediction, Leading to Better Health Outcomes for Hospitalized Patients

An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and treatment of delirium. The model identifies patients at high risk for delirium and alerts a specially-trained team to assess the patient and create a treatment plan, if needed.

AI-Human Task-Sharing could Cut Mammography Screening Costs by Up to 30%

The most effective way to harness the power of artificial intelligence (AI) when screening for breast cancer may be through collaboration with human radiologists - not by wholesale replacing them, says new research co-written by a University of Illinois Urbana-Champaign expert in the intersection of health care and technology.

AI-Powered Precision: Unlocking the Future of Immunotherapy through Immunogenomics, Radiomics, and Pathomics

A team of researchers from the Department of Diagnostic and Therapeutic Ultrasonography at the Tianjin Medical University Cancer Institute & Hospital, have published a review in Cancer Biology & Medicine. The paper underscores the potential of AI to decode complex biological data with unprecedented speed and accuracy.

SALSA: A New AI Tool for the Automated and Precise Analysis of Liver Tumors

Investigators of the Vall d'Hebron Institute of Oncology's (VHIO) Radiomics Group, led by Raquel Perez-Lopez, have developed SALSA (System for Automatic Liver tumor Segmentation And detection), a fully automated deep learning-driven tool for the precise and completely automated detection and monitoring of liver tumors (hepatocellular carcinoma).

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