Jean Coquet

Office X251
Biomedical Informatics Research
1265 Welch Road
Stanford, California 94305

+1 (650) 723-1831

jean.coquet@stanford.edu

Jean Coquet

Postdoctoral Research Fellow in computer science

Department of Medicine, Center for Biomedical Informatics Research (BMIR)

Boussard Lab

My research focuses on establishing novel strategies to assess and improve quality of health care delivery system with data science techniques using patient reported outcomes (PROs) and Electronic Health Records (EHRs). The methodologies I use involve advanced machine learning and Natural Language Processing (NLP) techniques for structured and unstructured health data.

During my PhD, my research was oriented towards the analysis of protein-protein interactions modeling, that has led to a global and systematic analysis of high-dimensional signaling model. The challenge was to find biological relevance in heterogeneous and strongly connected data. After started as a postdoctoral fellow, I leaded a study of bone scan quality metric for prostate cancer patients involving a risk stratification method and a NLP method based on Convolutional Neural Network (CNN) model. More recently, I also worked on a survival analysis showing an association between patient-initiated emails with overall 2-year survival in cancer patients receiving chemotherapy. This project inaugurates a new pathway to capture patient’s voice that may improve health outcomes.

Publications & Scientific Communication

Association of patient-initiated emails with overall 2-year survival in cancer patients receiving chemotherapy

Coquet J, Blayney DW, Brooks JD, Hernandez-Boussard T
2020
‹in revision›
Comparison of Orthogonal NLP Methods for Clinical Phenotyping and Assessment of Bone Scan Utilization among Prostate Cancer Patients

Coquet J, Bozkurt S, Kan K, Ferrari M, Blayney DW, Brooks JD, Hernandez-Boussard T

Journal of Biomedical Informatics (JBI), 94, pp 103184. 2019
‹10.1016/j.jbi.2019.103184›
Challenges in Measuring Guideline Adherence: Results of Bone Scan Utilization for Prostate Cancer Patients

Coquet J, Park JI, Bozkurt S, Kan KM, Ferrari MK, Brooks JD, Hernandez-Boussard T

AMIA Informatics Summit. 2019
KaSa: A Static Analyzer for Kappa

Boutillier P, Camporesi F, Coquet J, et al

Computational Methods in Systems Biology. Springer International Publishing, pp 285–291. 2018
‹10.1007/978-3-319-67471-1_6›
Identifying Functional Families of Trajectories in Biological Pathways by Soft Clustering: Application to TGF-β Signaling

Coquet J, Theret N, Legagneux V, Dameron O

Computational Methods in Systems Biology. Springer International Publishing, pp 91–107. 2017
‹10.1007/978-3-319-67471-1_6›
The smell of us – crowdsourcing human body odor evaluation

Benony M, Cardon M, Ferré A, Coquet J, et al

Human Computation, 3, pp 161–179. 2016
‹10.1007/978-3-319-67471-1_6›
Topological and semantic Web based method for analyzing TGF-β signaling pathways

Coquet J, Andrieux G, Nicolas J, et al

JOBIM. 2015
‹hal-01242893›

Awards & Volunteer projects

Project Manager of the film festival "Sciences en Court[s]": The festival allows doctoral students to make short films explaining their thesis work in a playful and educational way. 2015 - 2017
Best New Application, International Genetically Engineered Machine (iGEM) competition: Developer of a crowdsourcing web-based application with Django framework that engages volunteer smellers to characterize human sweat samples. This application was made as part of the International Genetically Engineered Machine (iGEM) competition. 2014

Scientific Popularization

Short Films Festival "Sciences en Court[s]": Une rencontre percutante