Cydar Medical Ltd. raised $11.5 million (£9.3 million) in a series A funding round which will allow it to advance its artificial intelligence (AI) surgical maps platform and bolster its ongoing commercial expansion.
With an eye toward the future, the U.S. Patent and Trademark Office (USPTO) is seeking comment on artificial intelligence (AI) technologies and inventorship issues that may arise as AI takes on a bigger role in innovation.
Shukun Technology Inc.’s recently approved AI-based system to assess coronary arteries can get results in minutes, significantly speeding up diagnostics.
With an eye toward the future, the U.S. Patent and Trademark Office (USPTO) is seeking comment on artificial intelligence (AI) technologies and inventorship issues that may arise as AI takes on a bigger role in innovation.
Bayer AG acquired Blackford Analysis Ltd., a British developer of artificial intelligence systems that help make diagnoses using medical images in the U.K. and U.S. The companies did not disclose any financial details. “This deal is part of our strategy to drive innovation in radiology, including the development and adoption of AI within the workflow, with the goal of ultimately improving patient care and advance our position in digital medical imaging,” Stefan Oelrich, a board member at Bayer AG and president of Bayer’s pharmaceutical division, told BioWorld.
Eyenuk Inc. is significantly extending the scope of its artificial intelligence system for the automatic analysis of retinal images, adding the diagnosis of age-related macular degeneration (AMD) and glaucoma to the EU approved uses of Eyeart AI.
Precisedx Inc.’s digital artificial intelligence (AI) platform better predicts the recurrence of early-stage breast cancer within six years than traditional testing, a study published in Breast Cancer Research found. Understanding which patients with early-stage disease face significant risk of their cancer returning is important for guiding selection of treatment. The system reduces the variability inherent in histological characterization and grading of breast cancer (BC) today, thereby improving prognostic accuracy.
The advantage of the U.S. FDA’s effort to regulate artificial intelligence (AI) in medical devices is that it is specific to medical devices and other medical products, but this vertical approach to AI regulation might soon become exceptionally complicated thanks to a new AI risk management framework posted by the U.S. National Institute for Standards and Technology (NIST). The NIST guideline is agnostic to the sector of the economy and thus may carry with it the expectation that developers of software as a medical device will hew to both the NIST framework and FDA regulations, a layering of requirements that could vastly complicate the task of developing and deploying these algorithms.
At a time when Chat GPT is making waves in the world of artificial intelligence (AI), new legislation is making the rounds in Washington that would allow an AI algorithm to write prescriptions for pharmaceuticals. Rep. David Schweikert (R-Ariz.) introduced H.R. 206 to the House Energy and Commerce (E&C) Committee Jan. 9, although at present the bill enjoys the backing of no other members of the House, suggesting that this legislation has a steep climb in front of it.
