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.
Microsurgical and Radiological Anatomy of Cerebral Sulci, Gyri, and Ventricles: The Rhoton-de Oliveira Course for Surgical Applications
Nov. 13-15, 2019; Jacksonville, Fla.
Complex Endoscopic Endonasal Surgery of the Skull Base
Nov. 14-16, 2019; Pittsburgh
2019 New Frontiers in the Diagnosis and Management of Movement Disorders
Nov. 16, 2019; Chicago
9th World Congress of Neuroendoscopy
Nov. 21-24, 2019; Orlando, Fla.
Mayo Clinic Multidisciplinary Spine Care Conference 2019
Nov. 22-23, 2019; Amelia Island, Fla.