I’m sure like the rest of us you’ve been overwhelmed with the vast amount of AI news from this year. Despite some exciting new possibilities, there have been a lot of concerns around the implications of AI in wider society: potential job losses, biased decision making, concerns around spread of misinformation, even existential risk. However, one area to remain optimistic about is the application AI in healthcare. At present, many healthcare systems around the world are overwhelmed and there is simply not enough resource to meet the demand of patients coming in. As a result, healthcare staff are stressed out, working long hours, and a lot of patients either have to wait too long to be seen or are not seen at all. In addition, even if a patient is seen, there are often issues with diagnosis (happening too late, being inaccurate, or a lack of diagnosis at all) and issues with treatment (no treatment available, available treatments being ineffective, treatments that cause further complications) So if patients are seen by healthcare professionals, many still either do not recover, leave with their health issues still present to some extent, or leave with an additional issue they now have to deal with. Although there are no silver bullets, when applying AI to healthcare one can imagine the extent to which these issues are relieved. AI is expected to be able to help with: Diagnosis of disease Discovery of drugs Individualised treatment plans Our understanding of human biology Predicting patient outcomes Aiding people with disabilities Assisting healthcare staff We’ll be diving deeper into some of these above categories, talking both about potential and current impacts that AI is having on healthcare. Diagnosis of disease Future diagnoses could involve supplying AI models with medical data on a patient and having the AI running calculations on the most likely diagnosis. There is potential for these models to achieve much higher precision and speed of diagnosis than is currently possible, allowing us to detect diseases both earlier and more accurately. Already, we have an example of a man whose dog was diagnosed with a tick-borne disease after falling sick. After starting treatment, the dog’s health continued to deteriorate, and blood tests showed more severe anaemia than before. Vets were unable to help with further options of diagnosis or treatment, so the dog owner put the blood test results into ChatGPT, which (after various prompting) correctly diagnosed the dog with immune-mediated hemolytic anemia (IMHA). Following this, the dog was put on appropriate treatment and made a full recovery. Click here to read the full story. Whilst we do not advise using AI chatbots for health diagnoses at this stage, what could be possible once these models are more refined for this purpose could be incredible. Drug discovery Another significant way AI may impact healthcare is through aiding drug discovery. It is expected that future AIs will be able to forecast drug-target interactions, identify potential drug candidates, and increase the speed of R&D cycles. So, it’s possible we may end up with more effective drugs that can treat a wider range of conditions and reach the market more quickly. One interesting example of AI already assisting with research into new drug candidates is from a project by Google’s AI team DeepMind, which they’ve called AlphaFold. There was previously a huge issue in biochemistry in that we had only modelled the 3D structure of a low percentage of all proteins in the human body. With human minds and existing technology, we were making a fairly slow pace. AlphaFold has now been able to sequence the 3D structure every protein in the human body. Of course, this has huge ramifications for the discovery of new drugs. In addition, another Google DeepMind project has discovered 2.2 million new materials using AI, which is equivalent to 800 years of human discovery. If you apply a similar approach to the discovery of new drugs then you can see the implications are vast. Click here to learn more. Aiding People with Disabilities There are already numerous examples of where AI has been able to help people with disabilities. For example, researchers have developed an implantable AI device that translates brain signals into modulated speech and facial expressions. As a result, a woman who lost the ability to speak due to a stroke was able to speak and convey emotion using a talking digital avatar. There is an equivalent story for a man who was unable to walk due to a spinal cord injury. With AI acting as a bridge between his brain and his muscles, he was able to walk again. Click here to read more about this story. Conclusions Despite the application of AI to healthcare being a relatively new field, already some of the progress has been astonishing, and the benefits we will continue to unlock are awe inspiring. Of course, with any new technology lies risks which we should remain vigilant about. But if it allows us, and those around us to experience more disease-free days and live longer lives, then surely it’s a future worth striving for. If you’d like to discuss this further, please reach out to HRW Innovation at innovation@hrwhealthcare.com Apply Now!