Explainable-AI image recognition startup ZAC initiates medical imaging for pathology
Z Advanced Computing (ZAC), the pioneer Cognitive Explainable-AI (Artificial Intelligence) (Cognitive XAI) software startup, will apply its Concept-Learning algorithms in medical imaging, starting with pathology, by expanding its medical team, including advisors, consultants, and collaborating medical facilities.
ZAC has developed and demonstrated disruptive technologies for recognizing and searching 3D objects and their details from any view direction in images and videos. For both the US Air Force and Bosch / BSH projects, ZAC has demonstrated major AI and Machine Learning (ML) breakthroughs, including using only a few training samples, and using much lower computing power (e.g., using only an average laptop with only CPU), for both training and recognition.
Bijan Tadayon, CEO, ZAC: "Our software will provide the tool to assist the pathologists make an opinion on an image more accurately and faster, which improves intra-reader and inter-reader variability for physicians and increases their daily performance.
ZAC owns a very strong IP portfolio with over 450 inventions, including 13 issued US patents. ZAC has an impressive team of scientists and developers. The development is headed by Saied Tadayon, a scientist and veteran software developer and a math prodigy, who ranked 1st as an undergrad at Cornell and got his PhD from Cornell at age 23.
Some other applications of ZAC tech are autonomous vehicles, e-commerce, ads, satellite/aerial imaging, security, and smart homes/appliances.
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