Dr. William (Bill) Bosl, Associate Professor of Health Informatics and Clinical Psychology at the University of San Francisco. His primary research focus is on clinical neurophysiology and neurodiagnostics. In 2018 Professor Bosl was appointed Visiting Associate Professor of Pediatrics at Harvard Medical School.
Dr. Bosl is leading a series of projects to discover patterns in infant EEG signals that can serve as biomarkers for autism and other neurodevelopmental pathology in collaboration with Boston Children’s Hospital (BCH) in Developmental Medicine. Dr. Bosl is also working with neurologists in the BCH Epilepsy clinic to find measures of epileptogenicity or tendency to have epileptic seizures.
Together with Professor and Program Director, 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 the 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.
- Director, MSHI Program
- PhD, Behavioral Neuroscience, Boston University School of Medicine
- PhD, Geophysics, Stanford University
- MA, Mathematics, University of Pittsburgh
- MS, Atmospheric Physics, University of Michigan
- BS, Chemistry, Miami University
- 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.
Bosl, William J. and Tager-Flusberg, Helen and Nelson, Charles A. "EEG Analytics for Early detection of Autism Spectrum Disorder: A data-driven approach" (2018). Scientific Reports. URL: https://doi.org/10.1038/s41598-018-24318-x
Chavakula, V., S. Fernandez, J. Peters, G. Popil, Bosl, W. J., S. Rakhade, A. Rotenberg, T. Loddenkemper. (2013). Automated quantification of spikes. Epilepsy and Behavior, 26(2).
Bosl, W. J., Mandel, J., Jonikas, M., Ramoni, R.B., Kohane, I.S., and Mandl, K.D. (2013). Scalable decision support at the point of care: A substitutable electronic health record app for monitoring medication adherence. Intert J of Med Res 2(2): e13.
Bosl, W. J. (2012). Neurotechnology and psychiatric biomarkers, in Ghista, D. (Ed.), Biomedical Engineering - Book 3; InTech Publishers.
Bosl, W. J.,Tager-Flusberg, H., Tierney, A., Nelson, C.A. (2011). EEG complexity as a biomarker for autism spectrum disorder risk. BMC Medicine, 9(18).
Kriete, A., Bosl, W. J., and Booker, G. (2010). Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses. PLoS Comput Biol 6, e1000820.
Bosl, W. (2007). Systems biology by the rules: Hybrid intelligent systems for pathway discovery and analysis. BMC Systems Biology, 1(13).
Bosl, W. & Li, R. (2005). Mitotic exit control as an evolved complex system. Cell, 121. 325-333.
American Medical Informatics Association
IEEE, Computational Intelligence SIG
International Neuropsychological Society
American Psychological Society