Understanding what determines accuracy can be confusing. But it doesn’t have to be! To help you understand the most common terms used in artificial intelligence, machine learning, and statistics, we have composed a glossary of the most common terms you’ll hear in the Medical Imaging
Artificial intelligence, neural networks and deep learning are the terms redefining medical proficiency and patient care in the healthcare industry Deep neural networks consist of multiple layers that allow for machines to sieve through vast quantities of data, solving complex problems and unlocking answers. It
By using the most advanced data parallelization technologies, we reduced our Radiology AI algorithm training time from days to 3 hours Motivation At Aidoc, we use deep learning to detect abnormalities in radiology scans, helping doctors improve the standard of care in clinics and hospitals
AI has become increasingly critical for radiologists in the 21st century. Aidoc CEO Elad Walach describes in Forbes magazine how radiologists can utilize AI to bolster three keys areas in medical care: Safeguarding health data – AI harnesses data to provide a fuller picture of a patient’s
Visual attention mechanisms are known to be important components of modern computer vision systems and are an inherent part of state-of-the-art achievements in almost all fields: object detection, image-captioning, and more. Most conventional visual attention mechanisms use medical image captioning and VQA (visual question answering)
