Radiology AI News
Harnessing AI in Medicine: Balancing Technological Innovation With Human Care
AI is set to revolutionize diagnostic imaging and personalized medicine while highlighting the enduring importance of human empathy and accessibility.
AI NLP Model Accurately Identifies Primary Cancer Types in Brain Metastases Cases
Researchers developed an AI tool using natural language processing to accurately identify primary cancer types in patients with brain metastases by analyzing clinical notes.
EMBL's Philanthropy-Fueled AI Strategy to Transform Life Sciences Imaging
EMBL launches a comprehensive AI strategy, supported by the Hector Foundation, to advance imaging and life sciences research.
Legal and Relationship Impacts of AI in Radiology: Expert Predictions
AI's integration into radiology is predicted to increase legal risks, impact patient relationships, and prompt regulatory action.
Hyperfine Enrolls First Patients in AI-Powered Portable MRI Study
Hyperfine has begun enrolling patients in the PRIME study to evaluate its next-generation portable MRI system for emergency triage.
AI Enhances Accuracy and Consistency in Embryo Health Assessment for IVF
Artificial intelligence-driven tools are improving embryo selection for IVF by making health assessment more consistent and precise.
Experts Propose New AI–Radiologist Division of Labor Models
Topol and Rajpurkar propose three models for dividing diagnostic tasks between AI and radiologists to improve workflow outcomes.
Data Transparency Gaps in FDA-Cleared Alzheimer’s Imaging AI Devices Highlighted
Research finds insufficient data transparency for FDA-cleared AI devices in Alzheimer’s imaging, raising bias and generalizability concerns.
AI-Generated Peer Reviews Threaten Trust in Scientific Publishing
AI models can write convincing fraudulent peer reviews that evade current detection tools, posing a new risk for research integrity.
Large Multimodal AI Models Compared for Lung Cancer CT Interpretation
A new study evaluates the diagnostic accuracy of three leading generative multimodal AI models in interpreting CT images for lung cancer detection.
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