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Juergen Hahn, Ph.D., professor and head of the Department of Biomedical Engineering at Rensselaer Polytechnic Institute (RPI), has been elected to the prestigious European Academy of Sciences and Arts for his outstanding and sustained impact on science and society. He will be formally inducted into the organization in 2025.

The Department of Biomedical Engineering at Rensselaer Polytechnic Institute has established a new master’s degree program that will prepare students for careers of biomedical data science, a fast growing engineering specialty.Those with expertise in biomedical data science are already in high demand, and that demand will  continue to rise in the future, said Juergen Hahn, Ph.D., head of the Biomedical Engineering Department.

Blood sample analysis showed that, two to five years after they gave birth, mothers of children with autism spectrum disorder (ASD) had several significantly different metabolite levels compared to mothers of typically developing children. That’s according to new research recently published in BMC Pediatrics by a multidisciplinary team from Rensselaer Polytechnic Institute, Arizona State University, and the Mayo Clinic.

TROY, N.Y. — Developing a physiological test for diagnosing autism spectrum disorder (ASD), one that measures certain components in the blood, has the potential to be a paradigm shift for diagnosing ASD. However, the large heterogeneity of how ASD affects individuals has long been viewed as a key obstacle to the development of such a test.

TROY, N.Y – Children with autism spectrum disorder (ASD) are often affected by co-occurring conditions, such as epilepsy, immune disorders, gastrointestinal problems, and developmental delays. According to research published today in Autism Research, creating a classification system for ASD based on co-occurring conditions could provide useful insights into the underlying mechanics of ASD and these conditions. 

TROY, N.Y. — Researchers at Rensselaer Polytechnic Institute who developed a blood test to help diagnose autism spectrum disorder have now successfully applied their distinctive big data-based approach to evaluating possible treatments.

A recent paper authored published in Research in Autism Spectrum Disorders discussed a test that can predict with approximately 90 percent accuracy whether a pregnant mother has a 1.7 percent or a tenfold increased risk of having a child diagnosed with ASD.

One year after researchers published their work on a physiological test for autism, a follow-up study confirms its exceptional success in assessing whether a child is on the autism spectrum.

An algorithm based on levels of metabolites found in a blood sample can accurately predict whether a child is on the Autism spectrum of disorder (ASD), based upon a recent study.