AI transforming data into health intelligence

October 10, 2017
By Bipin Thomas

In my previous columns, I introduced the transformational power of artificial intelligence (AI) technologies in the health care industry.

AI’s transformative potential comes from its ability to interrogate, parse and analyze vast amounts of data. From this information, AI systems can find patterns and links that would have previously required great levels of expertise or time from clinicians. For this reason, AI is particularly useful in providing diagnostics, creating personalized treatment plans and even helping physicians keep up to date with the latest medical research.



AI technologies such as machine learning and deep learning are poised to have a big impact in health care. One of the underlying issues is whether the data is ready for AI. Electronic health records, consumer medical devices and genomics are excellent data sources to begin with. It can be further strengthened with insurance claims, imaging and clinical research data. There is also the potential to mine massive amounts of online data to deliver intriguing results. The real opportunity of this data is not the patients who are already sick. It helps identify those who are currently not touching the system. AI is helping uncover the invisible patients based on that additional data set.

Delivering early and actionable intelligence
The treatment and prevention of rare and dangerous diseases often depends on detecting the symptoms at the right time. In many cases, early diagnosis can result in a complete cure. AI algorithms can quickly ingest millions of samples in short order and glean useful patterns. And unlike humans, they don’t lose their edge when they grow old. Several institutions and firms are investing in this scheme in developing health care solutions.

Researchers at Stanford University have created an AI algorithm that can identify skin cancer. They trained their deep learning algorithm with 130,000 images of moles, rashes and lesions. According to the results, its efficiency in diagnosing skin cancer rivals that of professional doctors. The researchers hope to make it available through a mobile app some time in the near future. This can be an opportunity to provide inexpensive screening to anyone with a smartphone.

Google is using machine learning to fight blindness in collaboration with the NHS. Researchers are training a deep learning algorithm with a million anonymous eye scans. This will help spot eye conditions such as wet age-related macular degeneration and diabetic retinopathy at early stages. According to the experts, in some cases, they might eventually be able to prevent 98 percent of the most severe visual loss.

The patients with chronic diseases cannot be managed in the four walls of a hospital or clinic. They have to be connected and monitored with medical devices from where they live. While medical devices can monitor heart rate, blood pressure, glucose and other functions, generating thousands of data points each day, clinicians don’t have time to analyze it. AI algorithms ingest this real-time and dynamic data along with electronic medical records, then find patterns and present to care teams with a list of effective therapies and treatment options.

As the next generation of both patients and caregivers, including clinicians, doctors, nurses, specialists, even executives and administrators, starts taking a foothold in the health care workforce, hospitals looking for a first-mover advantage already know that AI is on the verge of becoming a critical component across the entire organization, and not just information technology.

Bipin Thomas
Finding new patients, predicting diseases and presenting potential treatment options are just a few of the myriad ways AI will transform health care data. AI is exploding quickly and the health care industry is on the verge of making the solutions faster, better and cheaper. In another 10 years, AI technology-driven solutions may become the gold standard by which all others are judged.

About the author: Bipin Thomas is a renowned thought leader on consumer-centric health care transformation. Thomas is a board member of HealthCare Business News magazine and strategic advisor to HealthTap. Thomas is a senior executive at Flex, where he is leading business innovation by enabling intelligent products and connecting stakeholders across industries. Thomas is a former senior executive at Accenture and UST Global, where he implemented strategic digital initiatives across the care continuum.