Mayo Clinic scientists have developed a computational model that predicts brain age using a large collection of neuroimaging data obtained using FDG-PET (fluorodeoxyglucose positron emission tomography) and structural MRI (magnetic resonance imaging). The deep learning-based model tests the relationship between brain age gaps in various forms of dementia, including mild cognitive impairment (MCI), Alzheimer’s disease (AD), frontotemporal dementia (FTD), and Lewy body dementia (LBD), as well as in normal brains.
Wearable Device Clears a First ‘Milestone’ in Seizure Detection (Medscape; requires subscription):
A wrist-worn device that uses machine learning accurately detects different seizure types in findings that have the potential to revolutionize the management of patients with epilepsy.
“We have set a first benchmark for automatic detection of a variety of epileptic seizures using wearable sensors and deep-learning algorithms. In other words, we have shown for the first time that it’s possible to do this,” study investigator Jianbin Tang, MA, Data Science Project Lead, IBM Research Australia, Victoria, told Medscape Medical News. [Read more…] about Study: Wearable sensors and machine learning may well (one day) help detect a broad range of epileptic seizures
A Quarter Million Gamers Helped Build This Incredibly Detailed Map of the Brain (SingularityHub):
“In 2012, when Angry Birds was in its prime, Seung had an inspiration.
“What if,” he wondered, “we could capture even a small fraction of the mental effort that goes into Angry Birds (for brain mapping)? Think of what we could do.” [Read more…] about From Angry Birds to brain mapping: The Gamification of Neuroscience