Oh no, you have a gunshot wound and you’re bleeding out. You’re losing consciousness and they wheel you out to the operating room. As you’re about to pass out, you come face-to-face with the one operating on you: an AI robot? Have we really come that far? Remember when they did surgery on a grape? When an AI could be one of your surgeons, providing an end–to–end experience from pre-operative planning to post-operative care? When an AI knows what to do with medical information? Could generative AI be your new healer? Does an AI become a machine that uses another machine to cure you? AI isn’t something new, it’s been evolving for more than 60 years. But, it may have been possible that OpenAI’s release of ChatGPT changed the game for AI.
And generative AI has been evolving too. Photorealistic images, those Tom Cruise deepfake videos you keep seeing on the web, text that sounds way too human and more, they’re something to marvel at, based on how far we’ve come. So, as a human medical professional, what can you do and where you can go to find out how AI is penetrating healthcare? Let’s say your first stop is a lounge, where a couple of doctors are holding a differential diagnosis.
Maybe, it can go through a patient’s file to customize the devices for maximum performance. And if some medical device could have some performance issues, AI could be used to understand how the device’s lifespan can be extended and also ascertain if there could be any future defects. Then, hurry up to the radiology and pathology department.
Or it goes through a patient’s X-rays, MRIs, CT scans and other medical images to figure out what’s wrong with them. A high-resolution image can be the difference between life and death, literally, because there are even clearer aspects to an image that a regular medical image may not show that clearly. And it doesn’t have to be 2-D. Your once-traditional medical imaging data could have a holographic representation, giving surgeons a comprehensive understanding of a patient’s body.
The regulatory issues may be a bit unwelcoming, because a patient’s safety and a device’s efficacy are important. So, AI solutions need to be tested for a long time to make sure they’re ready. And AI has had problems in the past dealing with bias, misinformation and incorrect results, so it could be a complementary relationship between AI and healthcare professionals to figure out what’s wrong and what’s right.
