How AI would affect the healthcare that I am interested in over the next decade

Xinyue Liu
Sep 6, 2018 · 3 min read

When I worked as an intern in a rehabilitation center a few years ago, I witnessed how drugs could endanger people’s mind, but could not figure out how to help them out. I knew that those patients suffered a lot from similar emotional depress and were constantly beaten by them. So I wondered if negative feelings of human being could be detected, or behaviors could be predicted, those people would have stayed away from drug addiction before they even get started. With the help of AI, my thought would come true. An article released by Stanford Medicine, August 2, 2018, states that “children with autism were able to improve their social skills by using a smartphone app paired with Google Glass to help them understand the emotions conveyed in people’s facial expressions, according to a pilot study”. In this case, AI was trained to recognize eight core facial expressions, defined by the researcher. But in the case of drug addiction, AI could be trained to recognized negative feelings by associating them with specific facial expressions. We could also use AI to predict future behaviors if given enough data.

With the light of AI shining into the healthcare industry, UX designers are paying much attention to how AI would transform the healthcare industry and how we could design comfortable experiences for users of health care. So far, experts have predicted how AI could be used in different aspects of the healthcare, from prediction, diagnostic, treatment process, to preventing recurrence, health protection, and so forth. Some say AI will be exploited to help with analytics by incorporating big data to find out patterns of a symptom, a better approach to cure a known disease, etc. On the other hand, some say AI will turn a traditional medical device into a smart tool, such as the monitoring machines in the ICU room that identifies deterioration of a patient. From the article “10 Promising AI Applications in Health Care” of Harvard Business Review, May 1,0 2018, the authors identify the most potentially valuable AI application: Robot-assisted surgery, which would gain 40$ billions potential annual value by 2026. Three next following AI applications are virtual nursing assistants, administrative workflow, and fraud detection, of which expected annual value by 2016 are 20$ billions, 18$ billions, and 17$ billions respectively.

No surprise, the most hardcore and transforming AI tools would bring the highest benefit to the whole human being, however, it takes lots of researches and error testing before AI-based devices could be safely applied. Take the assisted surgery AI application as an example, since performing surgeries requires extreme accuracy on locating the problems, the robotics might need countless data to train for identifying the precise problem and locating the tiny lesions inside the patient’s body or brain. There, ethics remain. If things do go wrong during the surgery, who will be responsible for the error, of course not the AI. As known, Uber’s automatic drive vehicles had caught up in a few accidents because it is claimed that they were hacked. And higher risks come with the surgeries. As far as I am concerned, it still takes decades to examine before AI could be applied to such hi-tech area in healthcare.

In the meantime, AI applications used for diagnostic are being well exploited by some institutions. An article from MIT Technology Review, April 11, 2018, claims that FDA has approved an AI-powered diagnostic device to be used in ophthalmology diagnostic that doesn’t need a doctor’s help. The permission was given to a software program called IDx-DR, which can “analyze images of the adult eye taken with a special retinal camera. A doctor uploads the images to a cloud server, and the software then delivers a positive or negative result”. The article also points out that “the FDA cleared AI-based software to help detect stroke”. Compared to robot-assisted surgery, AI in medical diagnostics has much lower risks. With achievable skills and algorithms in machine learning and big data, no mention doctors or other medical professionals can help with interpreting the results to avoid false-positive situations, the AI-powered diagnostic will be exploited further into various aspects with the healthcare industry.

Advanced Design for Artificial Intelligence

A 15-week course focused on techniques for designing products powered by AI that form new relationships with users. Written by students of the Advanced Design for AI course at the University of Texas in Austin.

Xinyue Liu

Written by

Advanced Design for Artificial Intelligence

A 15-week course focused on techniques for designing products powered by AI that form new relationships with users. Written by students of the Advanced Design for AI course at the University of Texas in Austin.

Welcome to a place where words matter. On Medium, smart voices and original ideas take center stage - with no ads in sight. Watch
Follow all the topics you care about, and we’ll deliver the best stories for you to your homepage and inbox. Explore
Get unlimited access to the best stories on Medium — and support writers while you’re at it. Just $5/month. Upgrade