Researchers from the Yale University filed for protection of a multi-modal approach to predict the progression risk of a heart condition using artificial intelligence algorithms applied to cardiovascular videos.
The Trump administration released an action plan for AI, which includes an exports program for full-stack AI in areas such as health care. The announcement drew the support of the Advanced Medical Technology Association, which described the initiative as an accelerant for the use of AI in health care and a boon to patient outcomes.
The continuing proliferation of U.S. state privacy law drew the attention of developers of med-tech wearables for some time, but a recent Senate hearing delivered the news to Congress that a failure to preempt it will slow digital health innovation to a crawl.
Lunit Inc. reported a new collaboration with Microsoft Corp. July 2 to jointly develop medical AI programs accessible on Microsoft’s Azure cloud platform.
The Medical Device Coordination Group (MDCG) posted a guidance document tackling the interaction between the Artificial Intelligence Act and the twin EU regulations for devices and diagnostics, but the lack of standards for AI development promises to impede efforts to bring these AI algorithms to the European market.
The U.K. Medicines and Healthcare Products Regulatory Agency reported June 24 it joined a global regulatory network for AI that is part of the Health AI regulatory initiative – a program that will invite another nine regulatory agencies to take part in the initiative in the months ahead.
The U.K. Medicines and Healthcare Products Regulatory Agency opened a second round in its AI airlock program although this round, like the first round, will be limited to four applicants.
Deski SAS raised $6 million in a seed round to support the launch of its cardiac imaging software, Heartfocus, in the U.S. The AI-driven heart exam tool helps health care professionals perform echocardiograms from any ultrasound probe to enable the early detection of heart disease.
For years, the biopharma industry has spent increasing amounts of money on R&D without improving success rates, leaving many executives searching for new, more predictable drug development paths.
Researchers at the Massachusetts Institute of Technology and Recursion Pharmaceuticals Inc. have released an open-source AI model that can predict the binding strength of small molecules as well as structures of proteins and biomolecular complexes. The model, which is called Boltz-2 and was released by the research team on the developer platform Github on June 6, addresses a major bottleneck in drug discovery with its improved ability to predict binding strengths.
