Google's medical large language Med-PaLM 2 is coming to selected customers – This And More News In Digital Health This Week
Bertalan Meskó, MD, PhD
Director of The Medical Futurist Institute (Keynote Speaker, Researcher, Author & Futurist)
With the release of Med-PaLM 2, the new iteration of Google's medical large language model , the AI landscape is buzzing again. YouTube has become a treasure trove of insightful university lectures on ChatGPT and its contemporaries. I've spent countless hours this week absorbing this knowledge, as we find ourselves in the midst of a fundamental breakthrough that demands our attention and understanding.
However, as we explore these remarkable advancements, it is crucial to be aware of their limitations. While it is impressive that ChatGPT has recently passed the U.S. Medical Licensing Exam, relying on it in practical situations could have disastrous consequences .
Google announced it would allow some Google Cloud healthcare customers to test their medical large language model, Med-PaLM 2. "Med-PaLM 2 harnesses the power of Google’s LLMs, aligned to the medical domain to more accurately and safely answer medical questions.
As a result, Med-PaLM 2 was the first LLM to perform at an 'expert' test-taker level performance on the MedQA dataset of US Medical Licensing Examination (USMLE)-style questions, reaching 85%+ accuracy." As they mentioned, they need to learn how this tool can be harnessed to benefit healthcare workers, researchers, administrators, and patients.
Deeplearning.ai founder Andrew Ng described the five levels of automation in medicine in 2021. I like his approach as among various AI classifications this is the most useful from a practical point of view. The 5-level concept helps us find ways to utilize AI in everyday medical practice.
This article aims to depict in a concise and easy-to-grasp way how the human-AI collaboration will unfold in the field of medicine in the years and decades to come. It also features an infographic that helps in visualising the spectrum of automation.
We are in the midst of an industrial revolution. The impact AI will have on our everyday and professional lives can only be compared to the changes the Internet has brought to the world. We are at the dawn of a new era and our capabilities will be hugely enhanced by algorithms, machine- and deep learning.
The course was designed to provide a crystal-clear overview of the role artificial intelligence (AI) can play in medicine and healthcare. Just come as you are, no coding experience or special knowledge is needed!
The Future of Healthcare Bundle provides a valuable resource for healthcare professionals, investors, and entrepreneurs looking to stay ahead of the curve in the rapidly evolving digital health industry.
With its comprehensive coverage of the latest trends and developments, this bundle offers the insights and knowledge necessary to make informed decisions and capitalize on the opportunities presented by digital health.
领英推荐
It's good to see the BBC discussing digital health methods, especially when it comes to using just a smartphone to assess health issues. As someone with an elevated risk of blood clotting due to a genetic issue, this news is music to my ears:
"Scientists at the University of Washington used an iPhone to detect clotting in a single drop of blood. They used the device’s Lidar (light detecting and ranging) sensor, which uses pulsed beams to build 3D images of the phone’s surroundings."
A new study in The Lancet indicates that treating hearing loss may reduce the risk of dementia. Researchers examined data from over 437,000 people in the UK Biobank and found that using hearing aids lowered the risk of dementia to levels similar to those without hearing loss.
The study suggests that hearing loss may be the most impactful modifiable risk factor for dementia in mid-life and that hearing aids could be a minimally invasive, cost-effective treatment.
AI has the potential to be very useful in healthcare, but it can't replace the personalized, ongoing evaluations and reassessments conducted by physicians.
Its limitations include misinformation, algorithmic bias, and the inability to account for patient-specific factors. While insurance companies may be incentivised to use algorithms due to potential savings, this could have a negative impact on the quality of care and lead to increased medical liability.
MORE NEWS ABOUT THE FUTURE OF MEDICINE
FACING HARDSHIP? – Pear Therapeutics files for bankruptcy
EFFICIENT SALES – Why Virtual Reality and Podcasts Will Revolutionize the Healthcare Marketing Industry
HUGE MARKET – India’s top five digital health and wellness start-ups
--
4 个月RATE LIST OF iMD ACCOUNTS ???? VIP ? ?? (CONTAINING ALL THE CONTENTS) YEARLY PLAN *30USD* 6 MONTHS PLAN *25USD* 3 MONTHS PLAN *20USD* ?ALL USMLE ??? CONTENTS ? QUESTION BANKS ? HARRISON'S BOOK AND MORE JUST NEED YOUR EMAIL .. ?? _IN VERY DISCOUNTED PRICE_ THANKS?? WhatsApp ?? +989397636274
--
1 年AI in Health Care can bring higher information organization and technical advancement as long as the data is accurate and truthful to actual life and test events. Still, there is a long due diligence period on data collected from current practice and future innovations ?? . Onward and upward for humanity.
Bertalan Meskó, MD, PhD Thanks for Sharing! ?
Lean six Sigma Black belt Professional, SAFe POPM technology exploration
1 年Superb new era specially for cardio?