Dr. Hadley’s expertise is in translating big data into precision medicine and digital health. He earned his PhD in genomics and computational biology while at medical school at PENN, and he trained in clinical pathology while at residency at Stanford. His research generates, annotates, and ultimately reasons over large multi-modal data stores to develop clinical intelligence, identify novel biomarkers and potential therapeutics for disease.
His early work at the Center for Applied Genomics at The Children’s Hospital of Philadelphia resulted in a successful precision medicine clinical trial for ADHD (ClinicalTrials.gov Identifier: NCT02286817) for a first-in-class, non-stimulant neuromodulator to be targeted across the neuropsychiatric disease spectrum. As an early principal investigator at the University of California San Francisco, his laboratory was funded by the NIH Big Data to Knowledge initiative to develop the stargeo.org as an open curation resource to discover the functional genes and biological pathways that are defective in disease.
He went on to develop NIH-funded models of curation for clinical applications of digital health to more precisely screen, diagnose, and manage disease. He was repeatedly recognized by UCSF with various awards including the inaugural Marcus Award for Precision Medicine to develop a digital learning health system to use smartphones to screen for skin cancer as well as a pilot award in precision imaging to better screen mammograms for invasive breast cancer.
As a new faculty member of the University of Central Florida College of Medicine, he is pioneering a new Division of Artificial Intelligence to leverage the transformative power of AI from medical school through clinical practice. In general, the end point of his work is rapid proofs of concept clinical trials in humans that translate into better patient outcomes and reduced morbidity and mortality across the spectrum of disease.
- Hadley D, et al.: Patterns of Sequence Conservation in Presynaptic Neural Genes. Genome Biol. 2006;7(11):R105.PMCID: PMC1794582.
- Hadley D, et al.: Analysis of six genetic risk factors highly associated with AMD in the region surrounding ARMS2 and HTRA1 on chromosome 10q26. IOVS. 2010 Apr;51(4):2191-6.
- Hadley D, et al.: The impact of metabotropic glutamate receptor and other gene family interaction networks on autism spectrum disorders. Nat Commun. 2014 Jun 13;5:4074. PMCID: PMC4059929
- Hadley D, et al.: Precision annotation of digital samples in NCBI’s Gene Expression Omnibus, Scientific Data. Sci Data. 2017 Sep 19;4:170125. doi: 10.1038/sdata.2017.125.
- Bhattacharya A, …Hadley D. Precision Diagnosis Of Melanoma And Other Skin Lesions From Digital Images. AMIA Jt Summits Transl Sci Proc.2017; 2017:220-226.
- Wong, A., …Hadley, D:Development and Validation of an Electronic Health Record–Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment. JAMA Netw Open.2018 1(4), e181018. doi: 10.1001/jamanetworkopen.2018.1018
- Ding Y, ...Hadley D, Franc BL. A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain. Radiology. 2018 Nov 6:180958. doi: 10.1148/radiol.2018180958
Education & Specialties
Education, Training, & Research:
- M.D., University of PENN, Philadelphia, PA
- M.S.E., Systems Engineering, University of PEEN, Philadelphia, PA
- PhD., Genomics & Comp. Biology, University of PEEN, Philadelphia, PA
- Postdoc, Molecular Ophthalmology, University of PENN, Philadelphia, PA
- Laboratory Medicine
- Crowd-Assisted Deep Learning
- Translating Big Data into Precision Medicine
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