Predictives and Diagnostics
Past Pilot Grant Awards
» Predictives and Diagnostics / SPADA» Medical Technologies (Biodesign)
» Stanford Health Care Innovation Challenge
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Please see the individual program pages to find contact information. If you cannot find what you are looking for, please email us.
Email:SPADA, the Stanford Predictives and Diagnostics Accelerator, was established to assist interdisciplinary innovators in research, development and deployment of technologies that improve human health through disease prediction and/or diagnostics.
Translating optical coherence tomography to diagnose Meniere’s disease
Year: 2015
Investigator: John Oghalai, MD, associate professor of otolaryngology
Microendoscopic sarcomere visualization for the diagnosis, prognosis and monitoring of ALS
Year: 2015
Investigator: Scott Delp, PhD, professor of bioengineering and of mechanical engineering; Mark Schnitzer, PhD, associate professor of biology and of applied physics
Machine vision for broad microbial detection: A rapid and automated approach for identifying pathogenic bacteria through DNA melting
Year: 2015
Investigator: Samuel Yang, MD, associate professor of surgery
Multiplex detection and sequencing of the viral repertoire in clinical samples
Year: 2015
Investigator: Curt Scharfe, senior scientist in biochemistry; Justin Odegaard, MD, PhD, instructor of pathology; Benjamin Pinsky, MD, PhD, assistant professor of pathology and of medicine; Martina Lefterova, MD, PhD, clinical pathology resident
Creating a $150 autism diagnosis
Year: 2015
Investigator: Dennis Wall, MD, PhD, associate professor of pediatrics; Maude David, postdoctoral scholar in pediatric systems medicine
Assessment and prediction of age-related macular degeneration progression through quantitative imaging biomarkers
Year: 2014
Investigator: Daniel Rubin, MD, assistant professor of radiology and of biomedical informatics; Luis de Sisternes Garcia, PhD in radiology; and Ted Leng, MD, assistant professor of ophthalmology at the Byers Eye Institute.
Journal articles:
http://www.ncbi.nlm.nih.gov/pubmed/25301882
http://www.ncbi.nlm.nih.gov/pubmed/4237666
http://www.ncbi.nlm.nih.gov/pubmed/25062439
The diagnosis and characterization of major depressive disorder by applying machine learning methods to human neuroimaging data
Year: 2014
Investigator: Matthew Sacchet, graduate student in neurosciences; Gautam Prasad, PhD, psychology visiting scholar; Ian Gotlib, PhD, professor and chair of psychology.
First in-human clinical trial of manganese-enhanced MRI (MeMRI) to assess peri-infarct injury
Year: 2014
Investigator: Phillip Yang, MD, associate professor of cardiovascular medicine; Rajesh Dash, MD, PhD, assistant professor of cardiovascular medicine; Dwight Nishimura, PhD, professor of electrical engineering.
Development of non-invasive, laser-based breath-ammonia sensor for urea-cycle-defect diagnosis and monitoring
Year: 2014
Investigator: Gregory Enns, MD, director of the Biochemical Genetics Program and associate professor of pediatrics; Victor Miller, mechanical engineering PhD candidate; Mitchell Spearrin, mechanical engineering PhD candidate; Christopher Strand, mechanical engineering PhD candidate; Ron Hanson, PhD, professor of mechanical engineering.
Need Help Getting Started?
Education & Mentoring Program:
Anandi Krishnan, PhD
Research training, events, and workshops:
Jessica P. Meyer
(650) 498-6140
To find mentors, research jobs, and fellowships, log-in to CAP Network.
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