How Artificial Intelligence Is Changing the Healthcare Industry

Now more than just a well-known cinematic catchphrase, in the context of artificial intelligence (AI) and healthcare, “Come with me if you want to live” has never been this relevant.

Roughly 86% of healthcare providers, life science companies, and tech-oriented healthcare vendors have become involved with AI, based on CB Insights’ findings in 2016. Furthermore, according to a 2016 study by Frost & Sullivan, come 2021, the AI healthcare market share will grow to approximately $6.6 billion — an impressive compound annual growth rate of 40%.

Now, there is little doubt of this happening, as the world’s greatest minds continue to develop more AI solutions for the healthcare industry. One way AI is applied in the healthcare industry, for instance, is in detecting insurance fraud, a practice committed by a handful of deceitful providers with tremendous impact on both healthcare costs and quality of service. Another way is in managing population health: identifying patients with similar risk factors, measuring the effects of these risk factors (and corresponding interventions) over time, and so on.

In the meantime, let’s take a deeper look at three other ways in which artificial intelligence is pushing healthcare toward the next frontier.

1) Health monitoring and risk assessment

These days, it’s not uncommon to see health enthusiasts wearing the latest in health tracking technology on their wrists. Beyond simply providing assistance to them when they engage in exercise (e.g. tracking their heart rate while jogging), these wearable devices also store the users’ health information, allowing their respective physicians to accurately monitor and determine their current state of health, as well as prepare for potential health risks. A New York-based healthcare AI company called Prognos is taking this a step further, as it is currently working on developing “predictive models” that can gauge the chances of a patient experiencing a particular health event based on data from anonymous patients gathered by partner labs across the United States.

Another example of this is how the UK National Health Service is using the Google DeepMind platform for health risk detection, based on data collected via a mobile app. Meanwhile, IBM has made significant progress in its Watson Health initiative, which aims to develop a singular, all-encompassing database capable of reading and analyzing a patient’s symptoms, comparing it to a virtual library of clinical studies, patient records, and medical textbooks in order to identify the most likely diseases to manifest in the patient based on risk level. The company has partnered up with other brands such as Medtronic (for diabetic patients) and Under Armour (for fitness and nutrition) to further develop this program.

Finally, AI is also utilized by medical experts and specialists to accurately spot and diagnose cancer by taking medical images of the body. Geneticists and genomicists have even been using AI to take a closer look at a patient’s DNA in order to find early indicators of eventual diseases.

2) Drug discovery, design and development

As it turns out, AI is just as crucial and helpful in developing solutions as it is in identifying problems. Thanks to the adoption of AI, the process of developing medicine for serious illnesses can be made much more efficient and cost-effective.

In addition to the Watson Health program, IBM has also partnered up with Johnson & Johnson for more advanced drug development, as it looks into scientific research and analyzes them from an AI-empowered perspective.

Another company, Atomwise, was deeply involved in developing technology that could pinpoint specific molecules that could inhibit the invasion of Ebola in healthy cells. Given that at the time they were developing this (2014), the Ebola scare had grown into a full-blown, wide-scale panic, and Atomwise did not have the typically generous amount of time that such undertakings require. Thanks to predictive AI processes and a supercomputer-driven approach, they were able to cut down on the lengthy research cycle—14 years, according to CEO Abraham Heifets.

3) Automated consultation, diagnosis, and treatment development

AI has gotten so advanced that it has become possible to rely on this technology for outpatient treatment and care.

Take tech company, for instance, and its Molly program. Molly is an AI program that essentially functions as a “digital nurse.” In addition to its capacity to monitor the health of patients suffering from chronic pain and illnesses, Molly is equipped with the functionality to answer inquiries and even evaluate symptoms. It can also modify its recommendations and prognosis based on changes in patient data.

Another example would be KidsMD, an app developed by the Boston Children’s Hospital for Amazon Alexa in 2016. KidsMD can answer questions about medication guided by weight and age information, as well as advise parents on whether or not their child’s symptoms merit a visit to the doctor. Lastly, two tech companies, The Butterfly Network and iCarbonX, are making waves in the AI healthcare industry by developing better ultrasound technology and a big data platform for disease prevention, respectively.

As more and more breakthroughs in AI occur each year, we inch closer and closer to more effective and efficient means of disease treatment and prevention. And while AI can never truly replace actual human medical practitioners, it can at least help humanity say “Hasta la vista” to its most critical healthcare challenges.

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