From the October 2017 issue of HealthCare Business News magazine
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.
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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.