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.
2018 Advanced Endoscopic Skull Base and Pituitary Surgery
June 1-2, 2018; New York
2018 American Society for Stereotactic and Functional Neurosurgery Biennial Meeting
June 2-5, 2018; Denver
Complex Endoscopic Endonasal Surgery of the Skull Base
June 7-9, 2018; Pittsburgh, PA
2018 Annual Meeting of the Michigan Association of Neurological Surgeons
June 8-10, 2018; Thompsonville, MI
CARS 2018 Computer Assisted Radiology and Surgery
June 20-23, 2018; Berlin, Germany