Google Cloud Releases New Clinical Generative AI Tools at HIMSS24
At HIMSS, Google Cloud announced new AI features designed to assist providers, payers and any other healthcare organizations seeking to make better use of their clinical data.
At HIMSS, Google Cloud announced new AI features designed to assist providers, payers and any other healthcare organizations seeking to make better use of their clinical data.
Bill Fera — a principal and head of AI at Deloitte — said that the generative AI frenzy holds incredibly promising opportunities for health systems. He noted that in order for hospitals to succeed in the era of generative AI, they need to establish the right metrics for their pilots early on so they can quickly nix or scale them.
Munck Wilson Mandala Partner Greg Howison shared his perspective on some of the legal ramifications around AI, IP, connected devices and the data they generate, in response to emailed questions.
As more and more organizations integrate Generative AI with Configure, Price, Quote (CPQ) systems, they declare their belief that we can aspire to incredible advancements in human health and well-being through digital transformation.
In clinical trials, pharmaceutical companies are seeking to optimize operations and improve efficiency by automating and enhancing processes through Artificial Intelligence (AI) and Machine Learning (ML). One area where this can reap tangible benefits across clinical trials is in data processing. A typical clinical trial generates over 13,000 documents in various formats (text, voice, video, […]
The only way to effectively scale care coordination to meet the needs of digital consumers is through technology, combined with empowered staff and transformed processes.
Increasing innovation in, and consumer demand for, healthcare technology continue to transform the Medtech industry, including in digital health, wearables, diagnostics, telemedicine and other health IT solutions.
Executives at LRVHealth expect to see a continued focus on generative AI, increased enrollment in Medicare Advantage and more in 2024.
Google introduced a new suite of healthcare-focused generative AI models designed to speed up workflows for clinicians and medical researchers. Health systems and medical research organizations, including HCA Healthcare and BenchSci, have been testing these models since April.
Researchers recently tested ChatGPT’s ability to answer patient questions about medication, finding that the AI model gave wrong or incomplete answers about 75% of the time. Providers should be wary of the fact that the model does not always give sound medical advice, given many of their patients could be turning to ChatGPT to answer health-related questions.
We will highlight Build My Health's revenue practice management tools, which could help physician practices add up to $250,000 to their practices.
At RSNA 2023, AI startup Hoppr announced that it teamed up with AWS to launch a new foundation model. The product, named Grace, is a B2B model designed to help application developers build better AI solutions for the medical imaging field — and to build them more quickly.
In reality, the healthcare sector is, in many ways, the ideal place for AI to be used. After all, it’s one of the few industries with access to a treasure trove of precisely the kind of high-quality data with which AI operates best.
Ultimately, to get generative AI in healthcare right we need input from the clinicians who will use these tools – and who understand the ramifications of applying AI without first rigorously testing applications to ensure they are safe and provide clear clinical value.
No matter what camp healthcare providers sit in, it's important for them to understand how they can harness the power of responsible generative AI. Here we dive into some use cases to consider exploring and how it’s impacting healthcare – for the better.
A new study led by Stanford researchers tested four commercially available LLMs and found that they all could potentially cause harm by breeding inaccurate, racist information. For example, all models tried to justify race-based medicine when asked questions about calculating patients’ kidney function and lung capacity — two areas where race-based medicine practices used to be common but have since been scientifically refuted.