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The article explores the emerging role of AI in the hospital setting, the risk of physicians being replaced and provides research on perspectives from medical professionals and AI experts  
The combination of machine learning and radiomics can predict the molecular subtypes of medulloblastoma, paving the way for early diagnosis and better treatment of this common cancerous pediatric brain tumor, according to research presented last week at the American Medical Informatics Association (AMIA) meeting in San Francisco.  
In a perspective piece, Stanford researchers discuss the ethical implications of using machine-learning tools in making health care decisions for patients.  
Dr. Langlotz addresses the National Academy of Medicine’s National Cancer Policy Forum.  
Mar 28 2018 | AI in Radiology: Rise of the Machines | Posted In: News
Dr. Matthew Lungren on Stanford AI in Radiology