The founder and chief medical officer of Omniscient Neurotechnology commented on the areas of need with understanding the brain map and treating conditions with multiple pathway crossover. [WATCH TIME: 4 minutes]
WATCH TIME: 4 minutes
"It’s all great and well for machine learning to spit out 30,000 outputs, but we have to look at these things and say, ‘does this make sense? What does this mean? Why do we think this part of the brain is in the machine learning?’ Humans need to go back and translate it."
Over time, it has been shown that brain disorders involve multiple and different neural dysfunctions, including regional brain damage, change to cell structure, chemical imbalance, and/or connectivity loss among different brain regions. For example, Alzheimer disease involves many symptoms clusters, including memory loss, apraxia, language impairment, and executive dysfunction, along with neural abnormalities including damage in the hippocampus and neocortex. Gaining a full understanding of the brain map and the complexities within it remains a challenge for researchers, even as these diseases become more highly characterized.
For Michael Sughrue, MD, machine learning may be a key piece to simplifying how clinicians approach these disorders. Sughrue is the founder and chief medical officer of Omniscient Neurotechnology, a company dedicated to improving the brain map through means of big data approaches and “connectomics.” In an interview with NeurologyLive®, Sughrue discussed aspects the brain that remain unsolved, including the complexities associated with neurodegenerative disorders. He stressed the need to utilize the advanced technology being created, including machine learning and the capabilities of artificial intelligence.