ML Model Identifies Cancer Type-Specific Driver Mutations
Pohang University of Science and Technology
Predicting the carcinogenicity of tissue-specific driver mutations may help detect and intervene in the early stages of cancer development
Artificial Intelligence
An AI Invasion: Improving Breast Cancer Biopsies
Miriam Bergeret, MSc
Researchers report first-ever routine clinical use of an AI-based tool for breast cancer biopsies in a pathology lab
Breast Cancer Risk Models May Incorrectly Classify Many Women
UCLA Health
AI algorithms and imaging biomarkers may amp up the prediction accuracy of risk models
A Blood Test for Cancer Shows Promise Thanks to Machine Learning
University of Wisconsin-Madison
New blood test could lead to more affordable cancer detection at earlier stages
New Computer Program Learns to Identify Mosaic Mutations That Cause Disease
University of California - San Diego
An artificial neural network was trained to spot tiny mutations in genetic sequences better and faster than human eyes
Dr. AI, What’s My Diagnosis?
Technion-Israel Institute of Technology
A Technion-developed deep-learning system looks at breast cancer scans better than a human ever could
Intelligent Automation Improves Health Data and Patient Safety
Oleg Bess, MD
AI-driven technology can reduce duplicate patient records, overlays, and other patient identification issues
Integrated BioAI Platforms Address Drug Development Bottlenecks
Isaac Bentwich, MD
From artificial intelligence to patients-on-chip, new technologies decrease reliance on animal testing
Genes to Potentially Diagnose Long-Term Lyme Disease Identified
Mount Sinai School of Medicine
Findings could lead to new diagnostics and treatments for the hard-to-detect condition
Artificial Intelligence Methods May Replace Histochemical Staining
Intelligent Computing
Improving pathology workflows using a new deep learning-based virtual staining framework