Machine Learning Techniques Generate Clinical Labels of Medical Scans
Researchers used machine learning techniques, including natural language processing algorithms, to identify clinical concepts in radiologist reports for CT scans, according to a study conducted at the Icahn School of Medicine at Mount Sinai. The technology is an important first step in the development of artificial intelligence that could interpret scans and diagnose conditions.
From an ATM reading handwriting on a check to Facebook suggesting a photo tag for a friend, computer vision powered by artificial intelligence is increasingly common in daily life. Artificial intelligence could one day help radiologists interpret X-rays, computed tomography (CT) scans, and magnetic resonance imaging (MRI) studies. But for the technology to be effective in the medical arena, computer software must be “taught” the difference between a normal study and abnormal findings.
Click here to read more.
8th Annual EANS Young Neurosurgeons Meeting and EANS Research Course
March 22, 2018 - March 24, 2018; Oxford, United Kingdom
The Society of University Neurosurgeons Annual Meeting
March 22, 2018 - March 25, 2018; Dallas
ASN 2018 Annual Meeting
March 24-28, 2018; Riverside, CA
3rd Annual Principles and Techniques of Complex Spinal Reconstruction: A Hands-on Cadaveric Workshop
March 30, 2018 - March 31, 2018; New York
11th Annual Cervical Spine Research Society Hands-on Cadaver Course
April 12-14, 2018; St. Louis, MO
Be the first to reply using the above form.