Edelweiss: Psychiatry Open Access (ISSN 2638-8073)
Editor
Biography
Dr. William (Bill) Bosl is currently an associate professor
of Health Informatics and Clinical Psychology at the University of San
Francisco, where he is also the current and founding director of the master’s
degree program in Health Informatics. His primary research focus is in clinical
neurophysiology and neurodiagnostics. Projects to discover patterns in infant
EEG signals that can serve as biomarkers for autism and other
neurodevelopmental pathology continue with collaborations at Boston Children’s
Hospital (BCH) in Developmental Medicine. A proposal to move this work to the
bedside is a finalist for a BCH Innovation & Digital Health Accelerator
award. Bill is working with neurologists in the BCH Epilepsy clinic to find
measures of ‘epileptigenicity’ or tendency to have epileptic seizures.
Together with
Professor Andy Nguyen at USF, Dr. Bosl is working on a crowd-sourcing approach
to annotation of clinical EEGs for research for the American Society of
Electrodiagnostic Technologists. Other projects involve neurodevelopment in
premature infants (with Rutgers medical school) and emergence of neurological
impairment in Kenyan children following cerebral malaria (with Oxford
University). An early-stage effort to detect mTBI following concussive head
injuries via EEG analysis is starting to collect data. Clinical applications
for all of this work will require integration of EEG-derived information with
other patient data in Electronic Health Records, and presentation to
clinicians, topics that are being developed with the Computational Health
Informatics Program at Boston Children’s Hospital. Professor Bosl has recently
been appointed Visiting Associate Professor of Pediatrics at Harvard Medical
School.
Research Interest
Early detection of neurodevelopmental disorders using
nonlinear EEG analysis, Integrating behavioral informatics into primary care
for mental health screening, Informatics for global health, especially mental
and neurological impairment, Cognitive phenotypes, consciousness and
electrophysiology, Nonlinear signal analysis and machine learning in healthcare
systems.
