Deep learning to analyze neurological problems

Getting to the doctor’s office for a check-up can be challenging for someone with a neurological disorder that impairs their movement, such as a stroke. But what if the patient could just take a video clip of their movements with a smart phone and forward the results to their doctor? Work by Dr Hardeep Ryait and colleagues at CCBN-University of Lethbridge in Alberta, Canada, publishing November 21 in the open-access journal PLOS Biology, shows how this might one day be possible.

Using rats that had incurred a stroke that affected the movement of their fore-limbs, the scientists first asked experts to score the rats’ degree of impairment based on how they reached for food. Then they input this information into a state-of-the-art deep neural network so that it could learn to score the rats’ reaching movements with human-expert accuracy. When the network was subsequently given video footage from a new set of rats reaching for food, it was then also able to score their impairments with similar human-like accuracy. The same program proved able to score other tests given to rats and mice, including tests of their ability to walk across a narrow beam and to pull a string to obtain a food reward.

Full story at Science Daily