Heather Hsu, Assistant Professor of Pediatrics
Talk Title: Optimizing value-based care for health equity
Talk Abstract: Value-based care is often heralded as a potential mechanism to improve health equity through implementation of incentives for providers to intervene on adverse social conditions associated with poor health. My research agenda focuses on identifying opportunities for payment model improvement and addressing potential issues of measurement bias in accounting for social factors in value-based care.
Bio: Heather Hsu, MD, MPH is a pediatric hospitalist and health services researcher at Boston Medical Center and Assistant Professor of Pediatrics at the Chobanian and Avedisian School of Medicine. She is also Scientific Director of the Boston Medical Center Clinical Data Warehouse for Research. Dr. Hsu’s main research focus relates to how value-based care transformations affect health equity and the financial well-being of the healthcare safety-net
Marc LaRochelle, Associate Professor of Medicine, BU
Talk Title: Comparative Effectiveness Emulated Trials of Medications for Opioid Use Disorder (COMPEET MOUD)
Talk Abstract: This presentation will provide an introduction to COMPEET MOUD, a NIDA-funded R01 study. We are using the novel Massachusetts Public Health Data Warehouse that individually links multiple statewide datasets to compare the effect of different types of MOUD on treatment retention and overdose with benchmarking to a previously conducted RCT.
Bio: Dr. Larochelle is a clinician investigator with clinical and research interests on the recognition and treatment of opioid use disorders and improving outcomes for patients prescribed opioids for chronic pain. As a health services researcher, he aims to leverage insights from large data sources and translate the findings into interventions that improve the quality and value of health care delivered. He is a buprenorphine-waivered physician with an active outpatient general medicine and addiction practice and also attends on the inpatient Addiction Consult Service at Boston Medical Center.
Benjamin Linas, Professor of Medicine
Talk Title: Modeling to inform response to the syndemic of substance use disorders and infectious diseases in the U.S.
Talk Abstract: This talk will provide examples of the ways that simulation modeling can inform real-world decision making about the syndemic of drug use and infectious diseases in the U.S., including projections to population level outcomes, extending the time horizon of empirical studies, and exploring the importance of uncertainty on decision making.
Bio: Dr. Linas is an Infectious Diseases physician scientist focused on the overlapping epidemics (syndemic) of substance use disorders and infectious diseases. His research investigates the comparative- and cost-effectiveness of interventions to identify and treat OUD, HIV, and HCV in the real-world, where resources are limited and the best strategies for obtaining good outcomes are not certain. Dr. Linas works closely with the U.S. Centers for Disease Control and Prevention (CDC) to identify effective and cost-effective strategies for diagnosing HCV and linking infected individuals to care, and he works with the National Institute on Drug Abuse on multiple projects that employ methods of health economics and simulation modeling to investigate innovative models for delivering care to people with SUD.
Jonathan Jay, Assistant Professor, BUSPH
Talk Title: Using machine learning to examine social determinants of firearm violence
Talk Abstract: Urban firearm violence is closely linked with neighborhood physical conditions, but those conditions are challenging to study using traditional methods. Computer vision and urban imagery can support innovative study designs.
Bio: Dr. Jonathan Jay studies urban health, especially youth exposure to gun violence, as an assistant professor at Boston University School of Public Health. He works at the intersection of data science and community health, focusing on relationships between urban environments and health and safety risks. He is the principal investigator of a career development award from the National Institute on Minority Health and Health Disparities (NIMHD) to study multilevel strategies for reducing racial disparities in youth firearm injuries.
Nathanael Filmore, Associate Director, Boston Informatics Group, VA Boston Healthcare System
Adjunct Instructor, Chobanian & Avedesian Boston University School of Medicine
Talk Title: Toward an Oncology Learning Healthcare System in the National Veterans Affairs Healthcare System
Talk Abstract: I will discuss our efforts to develop a learning healthcare system for oncology in the national VA healthcare system, including using large VA databases to generate knowledge efficiently (e.g., prediction models, real-world evidence) and developing systems to deliver knowledge generated through research to clinical staff in a timely manner. I will also discuss our efforts to leverage Boston Medical Center’s diverse patient population for associated efforts.
Bio: I lead a research group that uses clinical, genomic, and imaging data, together with machine learning and statistical methods, in research to improve patient care. My group’s research portfolio includes (1) using data science to build predictive models and characterize clinical outcomes in Veterans with cancer; (2) developing new machine learning methods for clinical applications; (3) collating and sharing clinical, genomic, and imaging data on Veterans with cancer through the Precision Oncology Data Repository; and (4) establishing data science infrastructure at the VA. I also serve as site director for the VA/NCI Big Data-Scientist Training Enhancement Program. I hold a PhD in Computer Science from the University of Wisconsin, Madison, and received postdoctoral training in Biostatistics and Computational Biology at Dana-Farber Cancer Institute and Harvard School of Public Health.
Wendy Kuohung, Associate Professor of Ob/Gyn, Boston University Chobanian & Avedisian School of Medicine
Talk Title: Data Science in Gynecologic Emergencies
Talk Abstract: Ectopic pregnancy and ovarian torsion are two of the most challenging diagnoses in women’s health, and misdiagnosis may lead to loss of life or organ function. Data science approaches will improve the diagnosis and management of these poorly studied conditions, particularly in underserved communities.
Bio: Wendy Kuohung, MD is the Director of Reproductive Endocrinology and Infertility at Boston Medical Center and an Associate Professor of Obstetrics and Gynecology at Boston University Chobanian & Avedisian School of Medicine. Dr. Kuohung received her medical degree from the Yale School of Medicine and completed her residency in Ob/Gyn at BMC and fellowship training in Reproductive Endocrinology and Infertility at Brigham and Women’s Hospital. She is an expert in treating infertility, in vitro fertilization, fertility preservation, menstrual disorders, fibroids, endometriosis, mullerian anomalies, and minimally invasive and robotic gynecologic surgery. Her research interests lie in disparities in reproductive care, placental and reproductive tract development, and the microbiome of the reproductive tract.
Archana Venkataraman, Associate Professor of Electrical and Computer Engineering
Talk Title: Engineering Solutions for Brain Dysfunction
Talk Abstract: The Neural Systems Analysis Laboratory (NSA Lab) sits at the intersection of biomedical data, artificial intelligence, and clinical neuroscience. In this lightning talk, I will snapshot our recent and ongoing projects that develop new computational algorithms to better understand and potentially treat neurological and psychiatric disorders.
Bio: Archana Venkataraman is an associate professor of electrical and computer engineering and an affiliate faculty in the Departments of Biostatistics and Biomedical Engineering at Boston University. From 2016-2022, she was an assistant professor at Johns Hopkins University. Archana directs the Neural Systems Analysis (NSA) Laboratory, which develops new computational models and algorithms for biomedical data to better understand and treat brain disorders. Her work has yielded novel insights into autism, schizophrenia, and epilepsy, with the long-term goal of improving patient care. Archana has won numerous awards, notably an NSF CAREER and recognition by MIT Technology Review as one of 35 Innovators Under 35. Her research is supported by the National Science Foundation and the National Institutes of Health.
Brian Cleary, Assistant professor, CDS, BME, and Biology
Talk Title: The organizing principles of cells and tissues
Talk Abstract: I will discuss our work that aims to identify physical, physiological, and evolutionary factors that shape or give rise to phenomena of low-dimensionality among high-dimensional molecular features.
Bio: Dr Cleary is a Computational and Systems Biologist in the Faculty of Computing and Data Sciences, the Department of Biomedical Engineering, and the Department of Biology at Boston University. He received his PhD from MIT before establishing a lab as an independent Broad Fellow at the Broad Institute.
Xin Zhang, Distinguished Professor of Engineering
Talk Title: On the Edge of AI: When Deep Learning Meets MRI
Talk Abstract: The continuing developments in AI have allowed us to incorporate deep learning technologies into areas of medical imaging, specifically focusing on MRI. Our primary commitment involves implementing cutting-edge deep learning models to aid medical imaging tasks such as fast MRI reconstruction and MRI field-transfer reconstruction, with the prospect of universally extending our work to other MRI-based applications in the future.
Bio: Dr. Xin Zhang, Distinguished Professor of Engineering, leads Laboratory for Microsystems Technology (LMST) at Boston University that focuses on the broad areas of metamaterials and microelectromechanical systems. Her recent honors and awards include the Guggenheim Fellowship, ASME Per Bruel Gold Medal, IEEE EMBS Technical Achievement Award, STAT Madness All-Star Award, and Sigma Xi Walston Chubb Award for Innovation. She is a Member of the European Academy of Sciences and Arts, and Fellow of National Academy of Inventors, AAAS, AIMBE, APS, ASME, IEEE, and Optica.
