’s Jack McCarthy wrote an article that reviewed a recent report by a study panel of A.I. experts from a number of industries, including healthcare, titled “Artificial Intelligence and Life in 2030.” Late in the article, the author called out four healthcare-specific areas that he believes are ripe for A.I. applications: 

  • Clinical settings. McCarthy relayed the report’s assessment that EHR use has had its share of challenges, that the EHR market is controlled by a handful of vendors, that many users aren’t satisfied with existing interfaces, and that these and other issues contribute to the fact that the promise of A.I. hasn’t been delivered on. But that’s all going to change in the next decade and a half, wrote the author, and he appended that note with a direct, hopeful quote from the report: “The opportunity to exploit new learning methods, to create structured patterns of inference by mining the scientific literature automatically, and to create true cognitive assistants by supporting free­form dialogue, has never been greater.”
  • Healthcare analytics. “Traditional and non­traditional healthcare data, augmented by social platforms, may lead to the emergence of self-­defined subpopulations, each managed by a surrounding ecosystem of healthcare providers augmented with automated recommendation and monitoring systems,” noted the report. McCarthy cautioned that possibilities like these are burdened by the FDA’s glacial approval process for new diagnostic software and HIPAA demands that impede the delivery of patient data.
  • mHealth. The author gave an example of an exercise app that could create, presumably with A.I. (McCarthy doesn’t explicitly state it in this example), exercise schedules and coaching that are based on an individual’s personal data.
  • Elder care. McCarthy suggests that tomorrow’s senior citizens will find significant value in A.I.—using smart devices that will assist in a wide variety of household tasks, including meal preparation and personal hygiene—and that this will “reduce the need for hospital or care facility stays.”

Learn more about how machine learning could one day save your life. Download the “Introduction to Machine Learning inHealthcare” report now!