Patricia’s expertise is informed by roles ranging from Director of Data Analytics and Research at Digbi Health to Software Engineer at Ebates.com to Assistant/Associate Professor at USF. Her students are co-authors of her peer-reviewed journal articles, with work presented at conferences and published as web and mobile apps.
She and her students are working on an NIH project to identify actionable genomic factors influencing racial disparity in cancer outcomes. Their outside collaborations range from machine learning analyses of large EHR datasets for disease risk to development of a tablet app to identify Kenyan children in need of cognitive therapy. Her other research areas include computational biology, precision medicine and applications of genomics and proteomics to human health.
- Data analytics and machine learning: R, Python, SQL scripting
- Bioinformatics: genomics, microbiome, proteomics
- Electronic Health Records
- Software Development: Java, C++
- Application of data analytics including machine learning to the health domain to produce software tools that perform analyses for clinicians, researchers, and the public.
- Application of computational biology, algorithms, and mathematical models to biological problems and predictions, with focus on genomics, microbiome and nutrition analysis.
- Faculty Advisor for HIPSA (Health Informatics Professional Student Association)
- Chair, USF Digital Teaching & Learning (DTL) Committee
- Co-chair, SciPy Diversity Committee
- SONHP PEC Committee
- PhD, Computer Science with emphasis on Computational Biology, University of California at Davis
- Director of Data Analytics and Research, Digbi Health
- Associate Professor of Health Informatics, USF
- Assistant Professor of Computer Science, USF
- Research Assistant, Lawrence Berkeley National Laboratory
- Software Engineer, Ebates.com
Awards & Distinctions
- University of San Francisco Educational Effectiveness Award (SONHP PEC Committee)
- Francis-Lyon PA, Kumbhare SV, Kachru D, Uday T, Irudayanathan C, Muthukumar KM, Ricchetti RR, Singh-Rambiritch S, Ugalde J, Dulai PS, Almonacid DE. Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results from a Preliminary Retrospective Study. Frontiers in microbiology. 2022:394.
- Sinha R, Kachru D, Ricchetti R, Singh-Rambiritch S, Muthukumar K, Singaravel V, Irudayanathan C, Reddy- Sinha C, Junaid I, Sharma G, *Francis-Lyon PA, “Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study”, J Med Internet Res 2021;23(5):e25401.
- *Francis-Lyon PA, Malik F, Cheng X, Ghezavati A, Xin F, Cai R. “TRPV6 as a putative genomic susceptibility locus influencing racial disparities in cancer”, Cancer Prevention Research. 2020 May 1;13(5):423-8.
- Sarafrazi S, Choudhari R, Mehta C, Mehta H, Japalaghi O, Han J, Mehta K, Han H, *Francis-Lyon P, “Cracking the “Sepsis” Code: Assessing Time Series Nature of EHR data, and Using Deep Learning for Early Sepsis Prediction”, Computing in Cardiology Volume 46 (2019). Also presented as a poster at CinC 2019.
- Attiga A, Chen S, LaGue J, Ovalle O, Stott N, Brander T, Khaled A, Tyagi G, *Francis-Lyon P, “Applying Deep Learning to Public Health: Using Unbalanced Demographic Data to Predict Thyroid Disorder”, IEEE Information Technology, Electronics & Mobile Communication Conference Proceedings, November 2018.
- *Francis-Lyon P, Abubakar A, Attiga Y, Manjunath R, Ramasubramanian U, Chaudhuri V, Nguyen T, Xu X, Zeng S, “Tablet App for Child Cognitive Assessment in Low and Middle Income Countries”, IEEE Global Humanitarian Technology Conference 2017 Proceedings.
* corresponding author
Award-winning Student Presentations of Research
- Cheng X, Malik F, Ghezavati A, Xin F, Husary E, Francis-Lyon P. "Association between germline SNPs and cancer in African Americans." Poster presented at Graduate Student Academic Showcase 2019, April 2019. Won Change the World from Here Research Award.
- Iams T, Japalaghi O, Sarafrazi S, Amouzgar A, Francis-Lyon P, Horton R “A Cost Saving Medical Imaging App Using Transfer Learning and Active Learning.” App to classify medical images using Transfer and Active learning. Poster presented at CARD (Creative Activity and Research Day) 2019, April 2019. Won best poster, Graduate.
- Sarafrazi S, Han J, Domingo M, Chang M, Sharif O, Stott N, Brander T, Francis-Lyon PA, “Forecasting Model for Disease Propensity Using EHR Data” Development of an AWS production pipeline wrangling EHR data from different healthcare providers into a 70 million rows dataset for machine learning assessment of disease risk. Selected for a talk at CARD (Creative Activity and Research Day) 2019.
- Chaudhuri V, Arbatti L, Xiangyi, Xu X, Chen X, Kemisetti A, “Undiagnosed.” Team Dons won 3rd place in the very competitive Silicon Valley Artificial Intelligence hackathon.
- Shah R, Bajaj A, Alfero M, Horton R, Francis-Lyon PA, “Simulating a large dataset of ECG readings for MS training site,” Poster presented at USF Graduate Student Senate Project Showcase, April 2018. Won the award for "Excellence in Academic Research.”
- Attiga A, Chen S, LaGue J, Ovalle O, Stott N, Brander T, Khaled A, Tyagi G, Francis-Lyon PA, “Applying Deep Learning to Public Health: Using Unbalanced Demographic Data to Predict Thyroid Disorder with TensorFlow,” Poster presented at USF Graduate Student Academic Showcase April 2017. Won the award for “Academic Research that Changes the World from Here.”