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Workshop on COMP2CLINIC: Biomedical Researchers & Clinicians Closing The Gap Between Translational Research And Healthcare Practice - C2C 2020

24 - 26 February, 2020 - Valletta, Malta

In conjunction with the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSTEC 2020


Jason Moore
The Perelman School of Medicine, University of Pennsylvania
United States
Brief Bio
Jason Moore is the Edward Rose Professor of Informatics and Director of the Penn Institute for Biomedical Informatics. He also serves as Senior Associate Dean for Informatics and Director of the Division of Informatics in the Department of Biostatistics and Epidemiology. He came to Penn in 2015 from Dartmouth where was Director of the Institute for Quantitative Biomedical Sciences. Prior to Dartmouth he served as Director of the Advanced Computing Center for Research and Education at Vanderbilt University. He has a Ph.D. in Human Genetics and an M.S. in Applied Statistics from the University of Michigan. He leads an active NIH-funded research program focused on the development of artificial intelligence and machine learning algorithms for the analysis of complex biomedical data with a focus on genetics and genomics. He is an elected fellow of the American Association for the Advancement of Science (AAAS), an elected fellow of the American College of Medical Informatics (ACMI), and was selected as a Kavli fellow of the National Academy of Sciences.
Carly Bobak
Quantitative Biomedical Sciences, Dartmouth College
United States
Brief Bio
Carly A. Bobak is a current PhD. Candidate in the Quantitative Biomedical Sciences program at Dartmouth College and has an MSc. in Applied Mathematics from the University of Guelph. She is co-mentored by Dr. Jane E Hill (Professor of Engineering) and Dr. A. James O’Malley (Professor of Biostatistics). Carly emphasizes and advocates for the importance of interdisciplinary collaboration to increase the quality of research. She is currently investigating improved computational methods for the discovery of diagnostic biomarkers for Tuberculosis. Other researchers included in this effort have expertise in analytical chemistry, biostatistics, microbiology, computer science, engineering, and of course, infectious disease clinicians. Carly is a current fellow in of the Institutional Program Unifying Population and Laboratory Based Sciences award from the Burroughs Wellcome Fund and is also a Quantitative Biomedical Sciences fellow at Dartmouth College.
Kristine Ann Giffin
Biomedical Data Science, QBS at Dartmouth College
United States
Brief Bio
Kristine A. Giffin, PhD is currently a Lecturer in the Biomedical Data Science department and has been the Curriculum Director for the Quantitative Biomedical Sciences (QBS) Program at Dartmouth College since the founding of the program in 2011. The QBS PhD program encourages interdisciplinary research and cross-trains students in biostatistics, epidemiology, and bioinformatics. Recently, she has aided in the design and implementation of a QBS Health Data Science Master’s program and a QBS Quantitative Epidemiology Master’s program, which both accepted their inaugural class in the Fall of 2018. In addition to directing a number of QBS courses, she is active in program expansion, student and faculty relations, recruitment, and admissions. Kristine received her Ph.D. in Genetics at Dartmouth College through the Molecular & Cellular Biology program and her BS in Biology from Boston College. Her thesis work investigated approaches to ease the computational burden of detecting epistasis, or gene-gene interactions, in genome-wide genetic studies.
Marek Svoboda
Quantitative Biomedical Sciences, Dartmouth College
United States
Brief Bio
Marek Svoboda is a current MD, PhD candidate at the Geisel School of Medicine at Dartmouth. He is mentored by Dr. Giovanni Bosco as a graduate student in the Quantitative Biomedical Sciences program. After growing up in Czechia, he received his B.A. in Neuroscience and Behavior from Columbia University. He is interested in interdisciplinary approaches that combine molecular biology and computational analysis for the benefit of new translatable approaches in clinical treatment. In his current project, he studies gene interactions in a mouse model of autism using single cell RNA sequencing in order to identify novel therapeutic targets. Like Carly, Marek is also a fellow in of the Institutional Program Unifying Population and Laboratory Based Sciences award from the Burroughs Wellcome Fund.


Artificial intelligence (AI) approaches are a major component in healthcare across disease prediction, patient outcomes, image interpretation, and triaging capabilities. It is critical that clinicians become integral to the algorithmic development and clinical applications of this methodology. We are seeking speakers who are clinicians or researchers that collaborate at various stages during the design and implementation of novel computational approaches targeting rapid clinical translation, or those working at the intersection of bioinformatics and clinical practice. This workshop will solicit papers that have identified clinical needs that can be addressed by AI and that can provide insight into successes and failures of bringing findings into the clinic. We hope to encourage conversation around how improved collaborations can enhance health care systems.


- Impact of AI on Healthcare
- Timelines for Implementing AI in clinical research and the clinic including international variations
- Improving the interpretability of computational algorithms used in the biomedical and healthcare setting
- Complementary roles of physicians and AI in the clinic of the future
- Increasing the translation and trust of computational algorithms and tools for predicting patient/disease outcomes and supporting clinical decision making
- Integrating clinician input in the design of algorithms and tools for the biomedical field
- Addressing biases in machine learning in healthcare and biomedical research
- Methods in medical image interpretation
- Increasing treatment efficiency via methods targeted for patient triaging
- Methods for rapidly translating medical literature into practice
- Algorithms and tools for obtaining data driven insights from clinical notes


Paper Submission: January 5, 2020 (expired)
Authors Notification: January 13, 2020 (expired)
Camera Ready and Registration: January 17, 2020 (expired)


Tyler Jervis, Independent Researcher, Canada
Trang Le, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, United States
Ruowang Li, University of Pennsylvania, United States
Brett McKinney, University of Tulsa, United States
Curtis Petersen, Independent Researcher, United States
David Qian, Department of Radiation Oncology, Winship Cancer Institute of Emory University, United States
Christiaan Rees, .Geisel School of Medicine at Dartmouth, United States
Jeff Thompson, KUMC, United States


Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.


The proceedings will be submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (CPCI/ISI), DBLP, EI (Elsevier Engineering Village Index), Scopus, Semantic Scholar and Google Scholar.
After thorough reviewing by the workshop program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support.
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library (
SCITEPRESS is a member of CrossRef ( and every paper is given a DOI (Digital Object Identifier).


BIOSTEC Workshops - C2C 2020