Researchers can better analyze patient data to find better treatments. Public health systems can analyze geographically linked data to identify patterns and manage the spread of disease. Radiologists can use the combination of signal processing and augmented analytics to get a clearer picture of X-rays, ultrasounds, CTs, MRIs, and any other type of scan.
The FDA recently approved a machine learning-based clinical diagnostic tool to assist medical professionals with analysis, the first of ultimately thousands of possibilities.
Binah.ai’s unique combination of signal processing, artificial intelligence, machine learning, and proprietary algorithms plus medical data – structured, unstructured, or semi-structured – delivers the actionable insights necessary to make accurate healthcare decisions.
Binah.ai’s radiology solution is available out of the box. Research has revealed that 30% of CT and MRI images are being analyzed incorrectly by overworked doctors. Factor in the exponentially growing demand for screening for cancer and other disorders and the shortage of skilled radiologists. The benefits of a system that saves time and increases accuracy by being especially tuned for denoising and classification of medical imaging data are immediately apparent.