AI and the next health revolution

This article is more than 12 months old

Tech big boys and research start-ups already making inroads into how diagnosis and treatment of diseases can be improved

Your next doctor could very well be a bot.

And bots, or automated programs, are likely to play a key role in finding cures for some of the most difficult-to-treat diseases and conditions.

Artificial intelligence (AI) is rapidly moving into healthcare, led by some of the biggest technology companies and emerging start-ups using it to diagnose and respond to a raft of conditions. Consider these examples:

  • California researchers detected cardiac arrhythmia with 97 per cent accuracy on wearers of an Apple Watch with the AI-based Cardiogram application, opening up early treatment options to avert strokes.
  • Scientists from Harvard and the University of Vermont developed a machine learning tool - a type of AI that enables computers to learn without being explicitly programmed - to better identify depression by studying Instagram posts, suggesting "new avenues for early screening and detection of mental illness".
  • Researchers from Britain's University of Nottingham created an algorithm that predicted heart attacks better than doctors using conventional guidelines.

While technology has always played a role in medical care, a wave of investment from Silicon Valley and a flood of data from connected devices appear to be spurring innovation.

"I think a tipping point was when Apple released its Research Kit," said Forrester Research analyst Kate McCarthy, referring to a program letting Apple users enable data from their daily activities to be used in medical studies.


Ms McCarthy said advances in AI has opened up possibilities for "personalised medicine".

"We now have an environment where people can weave through clinical research at a speed you could never do before," she said.

AI is better known in the tech field for uses such as autonomous driving, or defeating experts in the board game Go.

But it can also be used to glean new insights from existing data such as electronic health records and lab tests, says Dr Narges Razavian, a professor at New York University's Langone School of Medicine, who led a research project on predictive analytics for more than 100 medical conditions.

"Our work is looking at trends and trying to predict (disease) six months into the future, to be able to act before things get worse," Dr Razavian said.

  • NYU researchers analysed medical and lab records to accurately predict the onset of dozens of diseases and conditions, including type 2 diabetes, heart or kidney failure and stroke. The project developed software now used at NYU which may be deployed at other medical facilities.
  • Google's DeepMind division is using artificial intelligence to help doctors analyse tissue samples to determine the likelihood that breast and other cancers will spread, and develop the best radiotherapy treatments.
  • Microsoft, Intel and other tech giants are also working with researchers to sort through data with AI to better understand and treat lung, breast and other types of cancer.
  • Google parent Alphabet's life sciences unit Verily has joined Apple in releasing a smartwatch for studies including one to identify patterns in the progression of Parkinson's disease. Amazon, meanwhile, offers medical advice through applications on its voice-activated artificial assistant Alexa.
  • IBM has been focusing on these issues with its Watson Health unit, which uses "cognitive computing" to help understand cancer and other diseases.

It is not just major tech companies moving into health.

Research firm CB Insights this year identified 106 digital health start-ups applying machine learning and predictive analytics "to reduce drug discovery times, provide virtual assistance to patients and diagnose ailments by processing medical images".

Maryland-based start-up Insilico Medicine uses so-called "deep learning" to shorten drug testing and approval times, down from the current 10 to 15 years.

Insilico is working on drugs for amyotrophic lateral sclerosis, cancer and age-related diseases, aiming to develop personalised treatments.

AI is also increasingly seen as a means for detecting depression and other mental illnesses, by spotting patterns that may not be obvious.

A research paper by Florida State University's Jessica Ribeiro found it can predict with 80 per cent to 90 per cent accuracy whether someone will attempt suicide as far off as two years into the future.


Facebook uses AI as part of a test project to prevent suicides by analysing social network posts.

And San Francisco's Woebot Labs this month debuted on Facebook Messenger what it dubs the first chatbot offering "cognitive behavioural therapy" online - partly as a way to reach people wary of the social stigma of seeking mental health care.

New technologies are also offering hope for rare diseases.

Boston-based start-up FDNA uses facial recognition technology matched against a database associated with over 8,000 rare diseases and genetic disorders, sharing data and insights with medical centres in 129 countries via its Face2Gene application.

Ms Lynda Chin, vice-chancellor and chief innovation officer at the University of Texas System, said she sees "a lot of excitement around these tools" but that technology alone is unlikely to translate into wide-scale health benefits.

One problem, Ms Chin said, is that data from sources as disparate as medical records and Fitbits is difficult to access due to privacy and other regulations.

More important, she said, is integrating data in healthcare delivery where doctors may be unaware of what is available or how to use new tools. - AFP

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