Electronic records pin broad set of health risks on genetic premutation

It was long believed the FMR1 premutation — an excessive number of trinucleotide repeats in the FMR1 gene — had no direct effect on the people who carry it. Until recently, the only recognized effect on the carriers of the flawed gene was the risk of having offspring with fragile X syndrome, a rare but serious form of developmental disability.

Lauren Bishop-Fitzpatrick, PhD – Slide of the Week

As a large wave of individuals with autism spectrum disorder (ASD) diagnosed in the 1990s enters adulthood and middle age, knowledge about the patterning of lifetime health problems will become increasingly important for prevention efforts. We retrospectively analyzed diagnostic codes associated with de-identified electronic health records using a machine learning algorithm to characterize diagnostic patterns in decedents with ASD and matched decedent community controls.

Using artificial intelligence for a big impact on neurodevelopmental research

Arezoo Movaghar earned her master’s degree in computer science and artificial intelligence. She built models based on the plentiful data found in medical records. So, when she came to UW–Madison as a PhD student and joined a research group, it surprised Movaghar to find out just how much data researchers in other fields collect.

Machine learning can detect a genetic disorder from speech recordings

How much information can we extract from a five-minute recording of someone talking? Enough to tell whether that individual may be genetically predisposed to some health complications, according to researchers at the University of Wisconsin–Madison’s …