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.

Consider these examples:

-California researchers detected cardiac arrhythmia with 97 percent accuracy on wearers of an Apple Watch with the AI-based Cariogram 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 Britains 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. McCarthy said advances in artificial intelligence has opened up new possibilities for personalized medicine adapted to individual genetics. We now have an environment where people can weave through clinical research at a speed you could never do before, she said.

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- Predictive analytics -

AI is better known in the tech field for uses such as autonomous driving. But it can also be used to glean new insights from existing data such as electronic health records and lab tests, says Narges Razavian, a professor at New York Universitys 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, 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.

- Googles 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 Alphabets life sciences unit Verily has joined Apple in releasing a smartwatch for studies including one to identify patterns in the progression of Parkinsons disease. Amazon meanwhile offers medical advice through applications on its voice-activated artificial assistant Alexa.

- Finding depression -

Artificial intelligence is also increasingly seen as a means for detecting depression and other mental illnesses, by spotting patterns that may not be obvious, even to professionals. A research paper by Florida State Universitys Jessica Ribeiro found it can predict with 80 to 90 percent 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 Franciscos 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 startup 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 centers in 129 countries via its Face2Gene application.

- Cautious optimism -

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, 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 health care delivery where doctors may be unaware of whats available or how to use new tools. Just having the analytics and data get you to step one, said Chin. Its not just about putting an app on the app store.

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Artificial Intelligence can predict whether someone will attempt suicide two years later: Study - Hindustan Times