The idea behind artificial intelligence insurance labs – where large language models and other AI technologies can be simulated and tested – is that they can improve the efficacy and fairness of predictive analytics,…
Continue Reading
In this interview, Dr. Samir Shah, Chief Medical Officer at Qure.ai, shares why achieving FDA approval is crucial for their AI solutions and for fostering trust in the technology. Dr. Shah discusses how their…
Continue Reading
Although hospitals are interested in digital health, the sales cycle for tech companies is notoriously long. One factor behind the length of this cycle is the critical need for hospitals to understand the credibility…
Continue Reading
Revolutionary Open-Source AI Model Card Released
The Coalition for Health AI (CHAI) has taken a groundbreaking step by releasing their artificial intelligence Applied Model Card on GitHub as an open-source resource. This innovative tool serves…
The Coalition for Health AI has announced the availability of the open-source version of its artificial intelligence Applied Model Card on GitHub. The healthcare industry-led coalition said Thursday it designed the card to enable healthcare…
Continue Reading
Hospitals and health systems have been discussing digital-first patient engagement for a while now, but fewer organizations than you might think have made huge strides forward on that front.Likewise, data-driven decision-making is a phrase…
Continue Reading
Healthcare organizations need more than just private and secure AI enclaves. They need flexibility to leverage different LLMs, transparency to trace recommendations back to models’ sources, and complete control over those sources and data.
Supplementing…
Matt A. Murphy, CEO and Co-Founder of Cascala Health
Joe Jasser, MD, MBA, Board Member for Cascala Health
It’s human nature that when we are told to do something, we want to know the reason why.
That’s…
Continue Reading
Large Language Models (LLMs) have shown promise in clinical applications through prompt engineering, allowing flexible clinical predictions. However, they struggle to produce reliable prediction probabilities, which are crucial for transparency and decision-making. While explicit…
Continue Reading
News
The House Task Force on Artificial Intelligence publishes its findings and recommendations, which include:
Challenges include data availability and quality, incomplete or inaccurate responses, non-individualized recommendations, lack of decision transparency, data privacy, interoperability with existing…
Continue Reading
