Behold

Behold.ai’s medical software uses cutting-edge artificial intelligence to help radiologists make better medical decisions. Behold.ai is deep-learning medical software that makes it easy for healthcare practitioners to identify diseases from radiology and camera image data.

It works by feeding the software algorithm hundreds of scans of healthy versus unhealthy lungs, for example, to teach the program how to identify a problem, and then improves on its own over time. In particular, the branch of AI known as deep learning has shown that computers can parse large volumes of data and, in the process, “learn” the salient features of images and find subtle patterns. Behold.ai empowers radiologists by providing suggestions based on prior training about similar cases, enabling radiologists to make better diagnostic decisions.

Behold.ai is an artificial intelligence-backed, computer-aided detection tool that integrates with existing picture archiving and communication system (PACS) software. Medical imaging technology — such as CT scans, MRIs, and X-rays — yields a lot of information that a radiologist has to analyze and evaluate comprehensively in a short time. In addition, a radiologist has to consider other factors besides the image and sometimes must operate under conditions of uncertainty. Behold.ai performs highly complex pattern recognition and highlights conspicuous abnormalities in medical scans and images such as lung nodules and cerebral aneurysms.

Behold.ai can also be used in preventative medical checkups, such as a mammography. For example, Behold.ai can be used to detect breast cancer by evaluating suspicious structures, such as microcalcification clusters and hyper-dense structures in soft tissue. Behold.ai uses artificial intelligence to help radiologists make better medical decisions by performing pattern recognition. It uses deep learning technology, which combines neural network architectures with massive computing power to automatically identify visual differences between healthy images and those with nodules, lesions, and other abnormalities.