MedPaLM: New AI Medical Chatbots Will Soon Be Better Than Waiting For A Doctor
Bertalan Meskó, MD, PhD
Director of The Medical Futurist Institute (Keynote Speaker, Researcher, Author & Futurist)
Large language models (LLMs), these excitingly versatile algorithms became a topic of general conversation in December 2022, when OpenAI released its GPT3 agent, also known as ChatGPT. LLMs are developed to carry on conversations in human-like ways, they are designed to understand complex queries and respond in a nuanced manner. We introduced potential medical use cases in this article.?
By now we all have a track record with some kind of a chatbot - if nothing else, a not-very-bright algorithm at a service provider. These interactions rarely left anyone particularly impressed, they sometimes contribute to solving our problems, but more often than not just result in a frustrated user leaving with a promise of contact from a human support staff member that may or may never happen.?
Large language models undoubtedly have changed this field forever, they are capable of such high-quality assistance that was never seen earlier. Only a few short weeks after the release of ChatGPT, Google/DeepMind announced the release of MedPaLM, a large language model specifically designed to answer healthcare-related questions, based on their 540-billion parameter PaLM model.
This model was trained on six existing medical Q&A datasets (NedQA, MedMCQA, PubMedQA, LiveQA, MedicationQA, and MMLU), and the developer teams also created their own HealthSearchQA, using questions about medical conditions and the associated symptoms.
At the moment MedPaLM can’t be tested by the general public, but you can read the researcher’s paper here.?
It “performs encouragingly but remains inferior to clinicians”
The document lists a number of possible medical applications, including knowledge retrieval, clinical decision support, summarisation of key findings in studies, and triaging patients’ primary care concerns among others, but also noted that MedPaLM “performs encouragingly, but remains inferior to clinicians.”
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The attached diagrams show that MedPaLM was still underperforming human clinicians in several areas:?
Large language models may easily be the best option we’ll have for medical consultations
Although the model is obviously not perfect, it does significantly better than any previous algorithms, and the field is improving fast. The LLM-based chatbot algorithms provide a never-before-seen quality of human-AI interaction.
This is what I think will happen: as these models get better and better, the risk of missing care due to capacity shortages in healthcare will soon outweigh the risk of the algorithms being wrong. We will be better off familiarising ourselves with communicating with such an LLM algorithm - purely because long waiting for medical answers due to the lack of healthcare personnel will pose a higher threat.?
Live consultation with a doctor will become a luxury in the 21st century, and any solution addressing this issue (from asynchronous telemedicine to medical chatbots) will actually improve our health prospects.
Founder & CEO - MedUKCare | Live-in Care | Home Care Services ??
1 年This is a very interesting article ?? Probably one way to make the healthcare work better and reduce waiting times to see a GP ????
Cambiando el mundo una persona a la vez - Universal Healthcare
1 年Let's train them! Will AI go to Med School?
Director | Coach | Writer | Technologist
1 年CharGPT can already answer general medical questions, I am taking anti-inflammatories post surgery so I asked ChatGPT verbatim the same question I asked both the discharging Dr, and the Pharmacist. All three were within reasonably expected parameters however ChatGPT was the only one that advised me to limit it's use if I am feeling comfortable.
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1 年Absolutely agree, Bertalan Meskó, MD, PhD. The enormous challenge of access to medical advice and expertise due to shortages of trained personnel will drive acceptance of AI-as-physician. The shortcomings are real but can be addressed. I would also note that the accuracy of human clinical decision-making in real-world situations when time is limited (a frequent occurrence) may be less than in controlled experiments.
Digital Adoption Researcher|Certified Search Marketer|Certified Digital Marketer|Pharma/Medical Solutions Marketer
1 年Interesting article Bertalan Meskó, MD, PhD. Well done! AI based algorithms will truly revolutionize service delivery in the healthcare industry. And, like you rightly discuss, it will be a 'choice for luxury' to physically consult a clinician when you can get somewhat similar service from an LLM -AI based medical chatbot. Moreso, with continued improvements in UX derived from this new technology. Benefits from leveraging this innovative technology abound. However, one major barrier esp. in the developing economies is the poor adoption of digital technologies. In this context, we just need to work on improving adoption of these revolutionary technologies if they are to make an impact.