According to a June 2019 article published inForbes Magazineunder the sponsorship of the Forbes Technology Council, the artificial intelligence-supported healthcare sector projections for 2025 are nearly $200 billion.Today’s AI-assisted healthcare developments largely center on improving results for patients at lower costs while aligning the interests of physicians, investors and other industry stakeholders. Here are a few of the leading developments that detail current and potential ways in which AI can assist physicians, staff and individual healthcare consumers to achieve better outcomes than ever before. 1. Socially assistive robots A recent article published under the auspices of Yale University’s education department, socially assistive robots (SARs) offer significantly different capabilities than physically assistive robots. SARs are programmed to interact with human beings to help resolve social, emotional and cognitive issues. Similar to a coach or mentor, SARs can help a child or adult learn to cope with real-world scenarios. The robots can also take on the role of an encouraging peer rather than an authority figure or a toy. The Forbes article notes that, depending on programming and design, SARs can also help to run diagnostic tests and support in-home healthcare needs. Some function as part of a clinical team, while others enhance health care in the workplace. Some robots can be interactive as well, such as a part of cognitive behavior therapy sessions. The Yale education team notes that SARs can help children get the individualized attention they need. For example, SARs could assist children who are learning English as a second language or provide kids with the motivation to adopt healthier lifestyle habits. An August 2018 article in Interesting Engineering reports that SARs can be helpful in serving three target populations: those who are elderly or aging, those who are cognitively disabled and those who require physical rehabilitation. 2. Medicine powered by data The digitization of medical records was only the first step in harnessing the power of emerging computer science to help patients gain greater control and understanding of their own healthcare information. Experts point out that easier access to one’s own medical records tends to result in a higher quality of care. Additionally, the use of big data analytics and data mining to crunch the healthcare-related facts and figures—which until recently were scattered over a proliferating number of unstructured databases—holds the promise of making potentially life-saving information accessible. Data-mining AI systems can draw information from electronically maintained medical records located anywhere, then organize them for use in further research. Researchers from Stanford School of Medicine notes that these AI capabilities, which continue to develop in sophistication and utility, can open up many frontiers in biomedical research and individual patient care. Moreover, the Stanford team points out that a main benefit of AI is the ability to pick out hidden patterns and associations among sets of data that may at first elude human researchers. AI systems can parse through large and cumbersome data sets and then deliver actionable results to researchers, leading to new clinical insights. So important is this field of study that major educational institutions offer an entire course in data-driven medicine. Stanford School of Medicine and University of Chicago School of Medicine are two institutions to offer data-driven courses. University of Chicago Medicine faculty says the use of data mining, machine learning, computer simulations, and other emerging AI functionalities are beginning to prove useful in producing new ideas about treating major diseases and infections and generating innovations in preventive care. 3. Better communication equals better care Closely related to today’s ongoing improvements in the organization and analysis of medical data are the improvements in medical communication AI can bring. Improved communication among providers, and from providers to patients, can sometimes mean the difference between life and death. A recent study by Johns Hopkins University School of Medicine in Baltimore revealed that close to 250,000 Americans die every year due to medical error. Fully four-fifths of these errors were shown to have stemmed from some type of miscommunication. Developers have created apps to assist doctors in gauging their own prescribing preferences alongside those of peers working with similar populations. Other apps increase accessibility and convenience by permitting patients and their healthcare providers to communicate and plan visits in real time. An October 2018 article published in the journal Nature summarizes recent research into AI’s use in doctor-patient communication. The authors found that, although such communication systems are still relatively new, they have already offered significant assistance in gauging risk factors across population groups, as well as in individualizing and customizing medical treatments in the interests of individual patients. They further note that innovations in data mining, visualization and other computational capabilities, when considered in tandem with improvements to assistive medical devices, continue to drive large-scale change in both the quality of patient care and the overall strategies of the medical field. The geocoding of medical data is one of many developments at the intersection of these innovations. An August 2017 article in Future Healthcare Today noted that geocoding—the data-driven precision transformation of a physical address into a geographic coordinate on a map—has already shown the potential to improve patients’ healthcare experiences, as well as the overall quality of healthcare data and its communication. For example, geocoding can combine data about a patient’s regular locations such as home or work with environmental information on factors such as air quality. This can help researchers determine which environmental factors may play a role in a variety of illnesses. Geocoded data can also assist first responders in saving lives by more easily locating a patient in need of urgent care.