Deep learning now tackling autism and matching monkeys’ vision

Two studies published this week provide even more evidence that deep learning models are very good at computer vision and might be able to tackle some difficult problems.

The study on computer vision, out of MIT and published in PLOS Computational Biology, shows that deep learning models can be as good as certain primates when it comes to recognizing images during a brief glance. The researchers even suggest that deep learning could help scientists better understand how primate vision systems work.

Figure 4.eps

Charts showing the relative performance of primates and deep learning models.

The genetic study, performed by a team of researchers from the Canadian Institute for Advanced Research and published in Science (available for a fee, but the University of Toronto has a relatively detailed article about the research), used deep learning to analyze the “code” involved in gene splicing. Focusing on mutated gene sequences in subjects with autism, the team was able to identify 39 additional genes that might be tied to autism spectrum disorder.

By now, the capabilities of deep learning in object recognition have been well established, and there is plenty of excitement among entrepreneurs and scientists about how it could apply in medicine. But these findings suggest that excitement has substance and the techniques can make meaningful impacts in areas have little or nothing to do with the web, from where many recent advances have emerged.