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Episode 45: AI doctors: how close are they? With Robert Sargsyan, CEO of Docus. Will AI doctors eventually replace human doctors? Are they already doing so? On one hand, people like the human touch of human doctors. On the other hand, human doctors get tired, are limited in terms of the amount of data they can handle and tend to be overstretched. So where are we with the development of AI doctors? Joining me is someone at the cutting edge of this fascinating topic, Robert Sargsyan, CEO of Docus.
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Waiting for emergency treatment, when you might already be in shock, can be a very distressing and lonely experience. A big part of the problem might be that you are feeling in the dark about what’s happening and how long you’ll be there. An already stressful situation could feel like an eternity. How can AI systems help here? Two men who have commercialised just such a thing are Aaron Patzer and Dr Justin Schrager, founders of the company Vital.
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Some have suggested that the medical profession is a force of resistance in AI adoption, that it is prioritizing the protection of jobs, potentially at the cost of patients
Is there any truth in that?
Or is the medical profession actually protectingpatients by resisting an overhasty rush to AI adoption?
With me is someone who is perfectly placed to discuss this, Dr Jethro Hubbard. He is a GP. And he was also instrumental in the introduction of the BMA policy on healthcare AI integration.
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AI has the potential to revolutionize clinical trials in many ways. It could make the development of new treatments faster, safer, cheaper and more personalised. One company in this space is Owkin, a unicorn startup based in Paris. With me is Dr Félix Balazard, Director ofOptimized Development Solutions.
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Clinical trials are the cornerstone of the development of new treatments. One can see them as a shining example of the scientific method in practice. One can also see them as phenomenally expensive, with a high rejectionrate and a record of passing treatments that are ineffective. So, how is AI being used to address these problems?
With me to discuss this is Dr Harsha Rajasimha, CEO of Jeeva Clinical Trials.
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Counterfeit medications and medical equipment is a huge global fraud. And it is deadly - counterfeit medications can contain incorrect ingredients and even harmful components. So how far is it possible to detectthis kind of fraud and how is AI a part of that effort? With me to discuss this is Roei ROY Ganzarski, CEO of Alitheon.
The Medical AI Podcast is one of Feedspot's top rated podcasts: https://blog.feedspot.com/uk_ai_podcasts/
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Imagine having crippling back pain, but there’s a four month waiting list for a physiotherpist. Alternatively, you have instant access to an AI-based physiotherapy system. 80% of adults have significant back pain at some point, so there’s an excellent chance that this kind of choice is one you will have to make.
But can it be made to work? Is the technology ready? Would it be accepted by governments and patients? Are there issues with patient safety?
With me is Finn Stevenson, who is working on precisely this idea. He is a former medic, and CEO of Flok Health.
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Episode 37: AI for psychotherapy. With Lindsay McKean, Psychotherapist
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The liver is a miracle of physiology, with over 1,000 known functions. This highlights the potential impact of liver dysfunction on various bodily systems. Also, liver disease is a major cause of death globally, and the numbers are on the rise. This adds up to a critical clinical need.
Dr Neil Guha is Professor of Hepatology at the University of Nottingham, an NHS consultant and Research scientist. He recently published an excellent paper in the journal of medical AI on a ML model to rate risk for liver disease.
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A year ago, very soon after the release of ChatGPT there was an article in Nature with the curious title… ChatGPT listed as author on research papers: many scientists disapprove
Since then, the use of LLMs in medical research has exploded, including as a coauthor of articles. But how is it being used? Does it matter? Does it undermine the human authors? And does it risk the quality of the research?
With me to discuss this is a brilliant up and coming researcher at the Universal Scientific Education and Research Network, Fiona Morrison.
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Personalised medicine has been promised as a coming revolution in healthcare. The concept goes all the way back to Hippocrates, around 400 years BC, but it is still very rare in clinical practice. Machine learning has been described as the key technology for personalised medicine - so are we finally about to see this revolution storming the gates? Discussing this with Felix is one of the key figures in this area, Richard Dobson, Professor of Medical Informatics at the Institute of Psychiatry, Psychology & Neuroscience, and Professor of Biomedical and Health Informatics at the Institute of Health Informatics, University College London.
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Are there ethical issues with medical AI that are unique? Any major technological development can have huge benefits and huge risks. And medical AI is no different. The benefits of medical AI are talked about endlessly. Much less so the risks. But what are those dangers?
The Declaration of Helsinki is widely regarded as the cornerstone of human research ethics. This a set of ethical principles regarding human experimentation developed originally in 1964 for the medical community by the World Medical Association. The fundamental principle is respect for the individual, his or her right to self-determination and the right to make informed decisions regarding participation in research. But what is the support adn the Declaration of Helsinki? Is it for purpose? Or is it actually highly questionable in some circumstances?
Joining Felix is Professor Erwin Loh, Chief Medical Officer for St Vincent's Health, Australia’s largest not-for-profit health care provider, Professor at Monash, Melbourne and Macquarie Universities and renowned author on medical AI.
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Medical AI might seem like a really new field. For example, the first medical AI product approved by the FDA was done so in only 2017. But does medical AI actually have a history that is far longer and richer than we might think? And are there important lessons to be learnt from that history?
Felix discusses with Professor Mark Braunstein, Author of "Health Informatics on FHIR". An author and thought-leader in the field, Dr. Braunstein is a professor of health informatics for the School of Interactive Computing in the College of Computing at the Georgia Institute of Technology where he teaches Introduction to Health Informatics, a popular graduate seminar, both on campus and as part of the OMSCS program. He is involved with HL7 and in various research projects at Georgia Tech, and works with and advises numerous community and industry groups.
Original music by Felix Beacher: https://youtu.be/JS93808r-W4
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