AUSTIN, Texas--(BUSINESS WIRE)--AI advancements have ascended to the point of ChatGPT passing the U.S. Medical Licensing Exam, opening the door for practice integration and patient treatment. According to Software Advice's 2023 Medical Chatbot Survey, nearly half of doctors (45%) believe ChatGPT is a valuable tool and 77% believe that AI-powered chatbots will be able to treat patients safely within the next 10 years. Today's chatbots are mostly used for admin work at medical practices, and they are great at automating work. The three most common patient uses for medical chatbots include scheduling appointments (72%), requesting prescription refills (66%), and providing requested data like medical history (63%). A notable 46% of chatbots are currently being used to assess symptoms and determine whether a patient needs immediate assistance or can wait for an appointment, but we predict this number will grow rapidly in the next few years.

As artificial intelligence continues to get more impressive, a lab out of Waterloo, Ont., is taking breast cancer research to new heights by working to help patients get proper treatment with their new technology. When patients get breast cancer, they typically undergo a type of imaging, like a magnetic resonance imaging or MRI, to look for cancerous tumors. The Waterloo lab has created "a synthetic correlate diffusion" MRI that is tailored to capture details and properties of cancer in a way that previous MRI systems couldn't. "It could be a very helpful tool to help oncologists and medical doctors to be able to identify and personalize the type of treatment that a cancer patient gets," Alexander Wong, professor and Canada Research Chair in Artificial Intelligence and Medical Imaging at the University of Waterloo, told Global News. Breast cancer is the second leading cause of death from cancer in Canadian women, according to the Canadian Cancer Society.

In a classic case of finding a balance between costs and benefits of science, researchers are grappling with the question of how artificial intelligence in medicine can and should be applied to clinical patient care – despite knowing that there are examples where it puts patients' lives at risk. The question was central to a recent university of Adelaide seminar, part of the Research Tuesdays lecture series, titled "Antidote AI." As artificial intelligence grows in sophistication and usefulness, we have begun to see it appearing more and more in everyday life. From AI traffic control and ecological studies, to machine learning finding the origins of a Martian meteorite and reading Arnhem Land rock art, the possibilities seem endless for AI research. The genuine excitement clinicians and artificial intelligence researchers feel for the prospect of AI assisting in patient care is palpable and honourable. Medicine is, after all, about helping people and the ethical foundation is "do no harm."

With Covid-19 cases surging in parts of the U.S. at the start of flu season, developers of artificial intelligence tools are about to face their biggest test of the pandemic: Can they help doctors differentiate between the two respiratory illnesses, and accurately predict which patients will become severely ill? Numerous AI models are promising to do exactly that by sifting data on symptoms and analyzing chest X-rays and CT scans. For now, the increased availability of coronavirus testing means AI is unlikely to be relied upon for frontline detection and diagnosis. But it will become increasingly important for figuring out how aggressively to treat patients and which ones are likely to need intensive care beds, ventilators, and other equipment that could become scarce if there's a Covid-flu "twindemic." "That's on the forefront of everyone's mind right now," said Anna Yaffee, an emergency medicine physician at Emory University who helped build an online symptom checker to assess Covid-19 patients.

One of the core principles of digital transformation is that it is meant to improve customer experience. But at the end of the day, humans are … wait for it … humans. Which means successful digital transformation isn't just a company's ability to earn customer relationship metrics. True success lies in a company's ability to make customer's lives better--whether those customers are buyers, patients, students, or otherwise. Let's face it: technology--especially AI--has gotten a bad rap in certain circles, and in some cases for valid reasons.

Tech these days is often accused of encouraging forms of addiction, but emerging "cyborg" technology may offer an answer for treating the opioid epidemic. Embedding microchips in the brains of addicts could help to, essentially, rewire them. He's among millions of people in America affected by what has become a national plague that kills hundreds each day. He hopes, though, that the computer chip in his brain can break him from addiction's hold. His dependence took hold after he dislocated his shoulder when he was 15.

Knowles said researchers then pulled the charts of those individuals the algorithm identified as likely having FH and found the system performed about as well as a human in diagnosing patients. "You could imagine this happening for … many potentially important conditions, not just FH," Knowles said. At the Cleveland Clinic researchers and doctors are using machine learning to predict the wellbeing of certain patients. "We're doing things to help us identify high-risk patients," explained Cleveland Clinic's Executive director of enterprise information management and analytics Chris Donovan. "So what patients are at risk of being admitted, what patients are at risk of deterioration in their care, or in their clinical condition and how do we intervene on those patients proactively."

In China, going to the hospital typically means that one could spend hours queuing for a consultation that lasts for just minutes. Now, a hospital in the southern metropolis of Guangzhou is looking to relieve the problem with artificial intelligence. The Guangzhou Second Provincial Central Hospital has incorporated AI into almost every area in its operations, including patient pre-diagnosis, CT scans, organizing patient records, and transporting operating-room supplies, the hospital said this week (link in Chinese). The country--which is challenging the US to be the world's preeminent AI powerhouse--hopes that robots can go some way in fixing the severe problem of doctor shortages. China has 2.3 physicians for every 1,000 people as of 2016, compared with Switzerland's 4.25 and the UK's 2.83, while its rapidly aging population is only adding more pressure to the health care system.

New York University's Langone Medical Center is developing one AI system to predict which patients are likely to develop the dangerous condition sepsis and another that alerts doctors to cases of heart trouble. "If you're admitted to the ER for pneumonia, the people who are treating you may not think about the fact that you also have congestive heart failure," says Michael Cantor, an internist and associate professor in the hospital's departments of population health and medicine. The system will go through each patient's record when they're admitted and automatically alert cardiologists to anyone who has heart failure, so they can advise on how to avoid treatments that might exacerbate that condition.

A London NHS hospital trust has teamed up with tech giant Google to share patient data so it can save more lives. Doctors at the Royal Free say partnering with the artificial intelligence arm of Google - DeepMind - could free up over half a million hours per year, currently spent on paperwork, towards direct patient care. Medical staff will get'breaking news' style alerts about their patients. Privacy campaigners are concerned about data breaches. Information on more than 1.6 million patients a year will be shared with a subsidiary of Google.