Artificial intelligence (AI) in healthcare refers to the use of AI technologies, such as machine learning, natural language processing, and computer vision, to analyze and interpret large amounts of data in order to improve patient care and outcomes. AI has the potential to revolutionize healthcare by providing insights and predictions that can lead to more accurate diagnoses, personalized treatments, and improved healthcare resource allocation. AI can be used in a variety of healthcare applications, including medical imaging analysis, drug discovery, personalized medicine, virtual assistants, predictive analytics, robot-assisted surgery, and remote patient monitoring. However, the use of AI in healthcare also raises concerns about privacy, bias, transparency, reliability, safety, and cost-effectiveness, which must be carefully considered and addressed to ensure that AI is developed and used in a way that is safe, effective, and beneficial to patients. While artificial intelligence (AI) has the potential to revolutionize healthcare, there are also several issues that must be addressed to ensure that it is developed and used in a way that is safe, effective, and beneficial to patients.

Jacob Kupietzky is President of HealthCare Transformation, a company dedicated to providing hospitals with experienced interim executives. Not long ago, if you wanted to explore the intersection of healthcare and artificial intelligence (AI), you'd be confined to the pages of science fiction. Not anymore: In recent years, AI has evolved from what's possible to what's practical, and consumers and practitioners alike have been increasingly drawn to the possibilities of how AI can revolutionize healthcare. While the promise of AI in this field is just starting to be realized, we are already seeing it have a real impact on patients' lives right now. Here are three ways AI is disrupting the practice of healthcare today.

Visualize a scenario where you are (god forbid) gravely ill, and yet you (miraculously) receive an accurate diagnosis with a recommended treatment plan within 10 minutes of reaching the hospital. This has, in actuality, been happening for a few years now with the help of Artificial Intelligence (AI). The University of Tokyo, in 2016 reported that Watson, IBM's cognitive supercomputer, correctly diagnosed a rare form of leukemia in a 60-year-old woman which doctors originally thought was acute myeloid leukemia. After examining 20 million cancer research papers in 10 minutes, Watson was able to correctly determine the disease and recommend a personalized treatment plan. AI and its related applications are changing healthcare as we know it. The advancements made in AI will revolutionize research and, ultimately, personalized medicine.

A new article published last week in the European Heart Journal discusses the use of drones for delivering life-saving automated external defibrillators (AED) to out-of-hospital cardiac arrest (OHCA) patients. As the study describes, "Early treatment in line with the'chain-of-survival' concept such as cardiopulmonary resuscitation (CPR) and defibrillation by an automated external defibrillator (AED) prior to ambulance arrival is associated with increased survival. Use of AEDs in the early-cardiac-arrest electrical phase can increase survival rates to up to 50–70%. Although hundreds of thousands of AEDs are available in high-income countries, their accessibility and use are still low." Thus, the investigators of the study designed a system to deploy drones to real-life suspected OHCA patients in order to determine whether this was a viable solution to the accessibility problem.

The promises of artificial intelligence (AI) have captured the interest and imagination of just about every industry, and healthcare is no exception. Radiology is an area that has already seen an impact from AI innovation. In fact, roughly a third of radiologists are currently utilizing AI in their practices according to a recent ACR Data Science Institute survey. However, those practices are only employing an average of slightly over a single algorithm, suggesting a limited number of available tools and significant room for growth once users find the right AI applications for their needs. Although AI is still in relative infancy, it is already proving useful in a variety of tasks and in service of some important goals in the healthcare field.

Healthcare is perhaps the most important sector in the U.S. economy. It is the largest: close to $4 trillion per year is spent on healthcare in the United States.

Digital technologies are redefining what is possible in healthcare and biology. Healthcare is perhaps the most important sector in the U.S. economy. It is the largest: close to $4 trillion per year is spent on healthcare in the United States. It employs more people than any other industry, accounting for 11% of all American jobs. Nearly one quarter of all U.S. government spending is on healthcare. At the same time, healthcare is the most broken sector in the U.S. economy. Healthcare costs have spiraled out of control in recent decades, from $355 per person in 1970 to $11,172 per person in 2018.

Each patient is different, with unique conditions so that the approach has to be specified to fully meet their needs.

On October 22, 2019, the Centers for Medicare and Medicaid Services ("CMS") issued a Request for Information ("RFI") to obtain input on how CMS can utilize Artificial Intelligence ("AI") and other new technologies to improve its operations. CMS' objectives to leverage AI chiefly include identifying and preventing fraud, waste, and abuse. The RFI specifically states CMS' aim "to ensure proper claims payment, reduce provider burden, and overall, conduct program integrity activities in a more efficient manner." The RFI follows last month's White House Summit on Artificial Intelligence in Government, where over 175 government leaders and industry experts gathered to discuss how the Federal government can adopt AI "to achieve its mission and improve services to the American people." Advances in AI technologies have made the possibility of automated fraud detection at exponentially greater speed and scale a reality. A 2018 study by consulting firm McKinsey & Company estimated that machine learning could help US health insurance companies reduce fraud, waste, and abuse by $20-30 billion.

Emerging technology has the potential to add efficiency and effectiveness to healthcare, according to Eric Topol, MD. Capabilities such as artificial intelligence, polygenic risk scores and digital health technology can equip physicians to improve and reduce the cost of care, while enabling them to better connect with patients, said Topol, the founder and director of The Scripps Research Institute. Much of care today is not based on provable facts, Topol noted at Liberation 2019, the annual meeting of Medecision, in Frisco, Texas. He cited an article by Hannah Fry, MD, published last month in The New Yorker, which detailed research that found that, of every 1,000 people taking statins for heart conditions over five years, only 18 will avoid a major heart attack or stroke. "Patients and clinicians exist in a world of insufficient data," Topol said.