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Skin cancer is one of the most common forms of cancer globally, with millions of cases diagnosed each year. Its prevalence is rising due to factors like increased sun exposure, aging populations, and lifestyle changes. The main types of skin cancer include melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC), with melanoma being the deadliest. Early detection is crucial for successful treatment, as skin cancer can often be treated effectively if caught early.
However, diagnosing skin cancer can be challenging due to the wide variety of skin conditions and the complexity of distinguishing between benign and malignant growths. Traditional methods of detection, such as visual inspection by dermatologists and biopsies, are time-consuming, subjective, and prone to human error.
AI systems, particularly deep learning and computer vision models, are being increasingly applied to help address these challenges. These AI tools can analyze medical images of skin lesions with high accuracy, sometimes surpassing dermatologists in diagnosing skin cancer. They can quickly identify suspicious moles or growths, enabling earlier and more accurate diagnosis. AI systems can also assist in classifying lesions into categories (benign or malignant) and track changes over time, improving long-term monitoring.
The potential benefits of AI in skin cancer detection include faster diagnosis, reduced workload for healthcare professionals, and improved patient outcomes through early intervention. As AI technology continues to evolve, it may become a key tool in reducing the global burden of skin cancer.
With Cody Simmons, CEO of Dermasensor
Check out other top-rated AI podcasts on FeedSpot:https://podcast.feedspot.com/uk_ai_podcasts/
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One of the landmarks in AI was the work on neural networks in the 1970s by Geoffrey Hinton, the "Godfather of AI". Thiswork took place at the University of Edinburgh. This laid much of the groundwork for the plethora of modern AI-based applications so academia and the corporate sector are two very different but essential types of crucible for AI research what is a relationship between them? Is it a loving partnership? Or is it more like a Hollywood marriage with crockery regularly being thrown against the wall? With to explore this important but under-discussed area is Prof Shai Shen-Orr, Associate Prof. at Technion, the Israel Institute of Technology.
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Longevity and immortality is a key theme in the earliest literature. But what does modern science have to offer to life extension? And in particular, has AI added anything new? With Felix is someone who is actively involved in this field, Dr Cory Goldberg.
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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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