PanGIA Biotech, Inc. ("PanGIA Biotech" or "Company") announced that two research abstracts have been accepted for ...

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 ...

TrialTranslator uncovers the survival gap for high-risk patients and offers a path to better cancer research. Study: Evaluating generalizability of oncology trial results to real-world patients using ...

Bottom line: A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), ...

What are the benefits and challenges of using multiomics approaches to discover cancer biomarkers? Multiomics means that scientists are measuring more than one class of analyte, such as DNA, RNA, or ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Machine learning and other forms of artificial intelligence have already been repeatedly proven to deliver faster, more consistent diagnoses than human physicians, but they may increase overdiagnosis ...

Please provide your email address to receive an email when new articles are posted on . Machine learning models can predict which patients receiving lung cancer therapy may need urgent care visits.

The evidence isn't there yet for routine use, but Michael Leapman, MD, urologic oncologist and associate professor of oncology at Yale School of Medicine, discusses what the future may hold for ...

We trained and tested ML systems that predict a deterioration in nine patient-reported symptoms within 30 days after treatments for aerodigestive cancers, using internal electronic health record (EHR) ...