An important thing to realize about the grandest conversations surrounding AI is that, most of the time, everyone is making things up. This isn't to say that people have no idea what they're talking about or that leaders are lying. But the bulk of the conversation about AI's greatest capabilities is premised on a vision of a theoretical future. It is a sales pitch, one in which the problems of today are brushed aside or softened as issues of now, which surely, leaders in the field insist, will be solved as the technology gets better. What we see today is merely a shadow of what is coming.

Summary: Using ECG data, a new machine learning algorithm was able to predict death within 5 years of a patient being admitted to hospital with 87% accuracy. The AI was able to sort patients into 5 categories ranging from low to high risk of death. If you've ever been admitted to hospital or visited an emergency department, you've likely had an electrocardiogram, or ECG, a standard test involving tiny electrodes taped to your chest that checks your heart's rhythm and electrical activity. Hospital ECGs are usually read by a doctor or nurse at your bedside, but now researchers are using artificial intelligence to glean even more information from those results to improve your care and the health-care system all at once. In recently published findings, the research team built and trained machine learning programs based on 1.6 million ECGs done on 244,077 patients in northern Alberta between 2007 and 2020.

Two of the most significant predictions for the new decade are that AI will become more pervasive, and the U.S. health-care system will need to evolve. AI can augment and improve the health-care system to serve more patients with fewer doctors. However, health innovators need to be careful to design a system that enhances doctors' capabilities, rather than replace them with technology and also to avoid reproducing human biases. A recent study published in Nature (in collaboration with Google) reports that Google AI detects breast cancer better than human doctors. Babylon Health, the AI-based mobile primary care system implemented in the United Kingdom in 2013, is coming to the U.S. Health-care is an industry in need of AI assistance due to a shortage of doctors and physician burnout.

The covid-19 pandemic has shown us how much health care is in need of not just tweaking but radical change. The pressure on global health systems, providers, and staff has already been increasing to unsustainable levels. But it also illustrates how much can be achieved in times of crisis: for example, China and the UK recently built thousands of extra beds in intensive care units, or ICUs, in less than two weeks. Health-care reform will need to spur a totally different approach to how care is organized, delivered, and distributed, which will be paramount in a (hopefully soon) post-covid-19 era. It's the only way to deliver the quadruple aim of health care: better outcomes, improved patient and staff experience, and lower cost of care.

Two of the most significant predictions for the new decade are that AI will become more pervasive, and the U.S. health-care system will need to evolve. AI can augment and improve the health-care system to serve more patients with fewer doctors. However, health innovators need to be careful to design a system that enhances doctors' capabilities, rather than replace them with technology and also to avoid reproducing human biases. A recent study published in Nature (in collaboration with Google) reports that Google AI detects breast cancer better than human doctors. Babylon Health, the AI-based mobile primary care system implemented in the United Kingdom in 2013, is coming to the U.S. Health-care is an industry in need of AI assistance due to a shortage of doctors and physician burnout.

Software and platforms powered by AI are expected to transform Asia's health-care landscape in the decade ahead, allowing health-care providers and government health-care authorities to increase capacity of service delivery, speed of diagnoses, quality of care, and overall patient health outcomes. The use of AI cannot be described as entirely nascent; indeed, it is already being widely used--particularly in developed Asia. Yet new use cases, new innovations, and new centers of AI adoption are emerging constantly, and the continuing urgency by governments and tech players to diffuse AI across health-care ecosystems will bring untold benefits to patients' lives across the region. AI is efficiently narrowing Asia's health-care gap. AI is an important and pragmatic solution for increasing the capacity and efficiency of health-care provision across the region.

My stomach is killing me!

Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time. In a new Viewpoint article published Dec. 10 in the Journal of the American Medical Association (JAMA), two AI experts at Washington University School of Medicine in St. Louis--Philip Payne, the Robert J. Terry Professor and director of the Institute for Informatics; and Thomas M. Maddox, MD, a professor of medicine and director of the Health Systems Innovation Lab--discuss the best uses for AI in health care and outline some of the challenges for implementing the technology in hospitals and clinics. In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients--such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.

Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time. In a new Viewpoint article published Dec. 10 in the Journal of the American Medical Association (JAMA), two AI experts at Washington University School of Medicine in St. Louis -- Philip Payne, PhD, the Robert J. Terry Professor and director of the Institute for Informatics; and Thomas M. Maddox, MD, a professor of medicine and director of the Health Systems Innovation Lab -- discuss the best uses for AI in health care and outline some of the challenges for implementing the technology in hospitals and clinics. In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients -- such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.

My stomach is killing me!