Artificial Intelligence and Healthcare in 2030

  • iReviews
  • December 03,2016
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Healthcare, whether it’s analyzing electronic health records (EHR’s) or providing in-home rehabilitation for elders, seems to be the perfect domain for artificial intelligence. According to a recent article published in the International Business Times, Stanford University experts have predicted advancements in AI and analyzed their inevitable impact on North America by the year 2030. The conclusion: health care has the most to gain and there is nothing to fear around robots taking over the world.

 

The first report is called, ‘Artificial Intelligence and Life in 2030’ and is part of a project called, ‘One Hundred Study on Artificial Intelligence (A100)’. As mentioned previously, healthcare seems to be the ideal sector for AI innovation. According to the report, “AI-based applications could improve health outcomes and quality of life for millions of people in the coming years – but only if they gain the trust of doctors, nurses, patients, and if policy, regulatory, and commercial obstacles are removed.”

 

Whether it’s assisting primary care doctors with electronic health records or reminding elders to take their daily meds, AI relies heavily on big data. According to a recent iReviews article, Neil Lawrence, Professor of machine learning at the University of Sheffield and part of Amazon’s AI team said, “these systems don’t just require more information than humans to understand concepts or recognize features, they require hundreds of thousands times more.” Lawrence says that huge tech giants like Google, Facebook and Microsoft are the perfect resource for AI. “They have abundant data and so can afford to run efficient machine learning systems.”

 

Giving artificial intelligence machines access to confidential patient records is a major hurdle. Stanford experts highlight the countless benefits AI brings to patient-level care citing “more finely-grained diagnostics and treatments,” but the industry doesn’t seem to be ready for change. With a small group of companies controlling the EHR market and patient confidential in question, AI technology stands to face layer upon layer of red tape. It appears to be a lost opportunity according to the Stanford panelists: “The opportunity to exploit new learning methods, to create structured patterns of influence by mining the scientific literature automatically, and to create true cognitive assistants by supporting free-form dialogue, has never been greater.”

 

Access to clinical records allows AI technology to find patterns in family history, symptoms, medications, etc. that human doctors may not be able to see. It also removes the human error element from the equation. Having a wealth of data to assist in diagnostics or treatment plans could save millions of lives. From warning doctors of allergies before prescribing new medications to providing surgical residents step-by-step procedures during an appendectomy, the possibilities are endless.

 

With that being said, AI has yet to be perfected. According to iReviews, AI is failing to progress for three specific reason: one, artificial intelligence requires a ton of ever-changing hard-to-get information; two, AI is unable to multi-task; and three, there needs to be more focus on how these systems reach their final conclusions.

 

In the realm of collecting an abundance of data, Lawrence mentions that it becomes exponentially more difficult to harness information in specialized fields like healthcare. AI, for example, is being used for machine vision tasks such as searching for tumors on x-ray scans. Lawrence, referencing the difficulty in securing data in healthcare said, “It’s generally considered unethical to force people to become sick to acquire data.”

 

New AI technologies, especially in the healthcare setting, require access to an abundance of patient data. With the FDA reluctant to approve diagnostic software and HIPPA legally protecting patient privacy, AI faces an uphill regulatory battle. AI relies heavily on big data and it just so happens that healthcare data is a heavily protected resource. Only time will tell whether or not the risk of having groundbreaking technology outweigh patient confidentiality.