Nooshin Abbasi, MD, MPH
Dr. Abbasi received her MD and MPH degrees from Tehran University of Medical Sciences in 2018. She then joined Montreal Neurological Institute, McGill University as a Post-Doctoral Research Fellow between 2018 and 2021 where her research primarily focused on using machine learning tools on large datasets to uncover multivariate relationships between the human genome and brain imaging. She has developed expertise in studying complex datasets involving multiple imaging modalities, network neuroscience, multivariate statistics, and genomic informatics.
Elvira Budiawan, MS
Elvira obtained her Master’s in Biostatistics – Statistical Genetics track from Columbia University, New York, and her Bachelor’s in Biochemistry with minor in Chemistry from University of Washington, Seattle. Currently, Elvira is a Research Assistant II at the Center for Evidence-Based Imaging of Brigham and Women’s Hospital, where she uses statistical analysis, machine learning, and natural language processing to model and analyze medical reports to improve evidence-based practice, as well as quality and patient safety.
Laila Cochon, MD, MPH, PhD
Dr. Cochon completed her MD training at Universidad Iberoamericana UNIBE in Santo Domingo, Dominican Republic. She obtained a masters degree in Emergency Medicine and Critical Care, as well as Clinical Research in the Universitat de Barcelona, Barcelona, Spain where she also pursued her PhD in Translational Medicine. Currently, Laila is an informatics research fellow at the Center for Evidence-Based Imaging of Brigham and Women’s Hospital/Harvard Medical School where her research mainly focuses on the use of healthcare IT (electronic health record, clinical decision support systems, machine learning, natural language processing) and its use to further enhance evidence based practice as wells as quality and patient safety. She recently completed an MPH with a focus on Clinical Effectiveness at Harvard School of Public Health.
Mahsa Eskian, MD
After graduating from National Organization for Development of Exceptional Talents(NODET), Dr. Eskian received her MD degree in 2018 from Tehran University of Medical Science. She conducted several research projects as a research assistant in Molecular Immunology Research Center and Sina Trauma and Surgery Research Center. Currently she is working as a postdoc research fellow in Center of Evidence Based Imaging at BWH, focusing on the field of diagnosis and survival prolongation of high burden and critical disease.
Isha Gujrathi, MD
Post-Doctoral Research Fellow
Dr. Gujrathi is MD Radiologist from India who is currently working as a Post-doctoral research fellow at the Center of Evidence Based Imaging of the Brigham and Women’s Hospital / Harvard Medical School. Her research projects focus on radiology image reviews and report analysis to standardize image interpretation. She is also closely working with the machine learning team on projects involving liver segmentation. Prior to joining CEBI, she was working as a research assistant at the Mount Sinai Hospital, University of Toronto where she worked closely with the Machine learning team to build a convolutional neural network for detecting prostate cancer. She will be taking a Summer course for Program in Clinical Effectiveness to enhance her research portfolio.
Raein Hashemi, MS
Research Assistant II
Raein received his Bachelors Degree from University of Tehran in Computer Science (Software Engineering) and his Masters Degree from Northeastern University in Medical Informatics and Data Science. Raein was a Research Assistant at the Computational Radiology Laboratory (CRL) of Boston Children’s Hospital. Currently, he is a Research Assistant at the Center for Evidence-Based Imaging (CEBI) of Brigham and Women’s Hospital. At CRL, Raein developed new deep learning strategies for enhanced fetal brain MRI segmentation, as well as brain tissue and lesion segmentation. At CEBI, he is developing new machine learning, deep learning and natural language processing techniques for the analysis of medical images and reports. His research focuses on clinical decision support systems and AI in healthcare.
Elias Kikano, MD
Dr. Kikano completed his medical school and diagnostic radiology residency at Case Western Reserve University in Cleveland, OH. He finished his clinical fellowship in Abdominal Imaging and Intervention at Brigham and Women’s Hospital/Harvard Medical School in 2022. He is a current informatics research fellow at the Center for Evidence-Based Imaging. His interests include leveraging healthcare software/electronic medical records for improving quality and patient safety as well as evaluation of radiology diagnostic error.
Kimtee is currently a Harvard College undergraduate student, concentrating in Human Developmental and Regenerative Biology with a secondary in Global Health and Health Policy. She is driven by the pursuit of improving healthcare access and delivery in underserved communities. Previously, Kimtee contributed to stem cell regeneration and imaging-based research in the Mariani Lab at USC. As a CEBI research trainee, she reviews and analyzes scientific literature to compose a manuscript on enhancing medical informatics integration.
Andro Licaros, MD
Dr. Licaros is a diagnostic radiologist who completed his training at the University of the Philippines – Philippine General Hospital. He is currently a post-doctoral research fellow at the Center for Evidence-Based Imaging (CEBI) at the Brigham and Women’s Hospital / Harvard Medical School. His research projects have included quality improvements in radiology through effective communication of critical findings as well as neuroradiology imaging reviews. At CEBI Dr. Licaros’ primary interests are on projects that optimize healthcare IT, imaging and reports analysis, as well as artificial intelligence.
Atul Shinagare, MD
Associate Professor in Radiology
Dr. Shinagare is a Staff Radiologist at Brigham and Women’s Hospital, Senior Physician at Dana-Farber Cancer Institute, faculty at the Center for Evidence-based Imaging and Assistant Professor of Radiology at Harvard Medical School. He also serves as the Radiology Quality and Safety Officer and Associate Fellowship Director of the Cancer Imaging Program. Dr. Shinagare’s interests pertain to use of evidence-based medicine, radiomics and informatics to make imaging more efficient and reduce the unwarranted variability in radiology reports. In my role as Radiology Quality and Safety Officer, I strive to standardize the imaging techniques, imaging interpretation and reporting to make radiology reports more clear and minimize the errors.
Luca received his Bachelor’s Degree from Boston University in Athletic Training and joined CEBI shortly thereafter to pursue his passion for quality improvement and evidence-based care in medicine. His work is mainly focused on improving patient experience and standardizing follow-up care in radiology. He also serves as a curator for the Harvard Library of Evidence.
Nicole Vetrano, MHA, BS, RT(R)
Nicole Vetrano is the CEBI Program Manager as well as the current Project Manager for the Harvard Medical School Library of Evidence. Nicole attended Massachusetts College of Pharmacy and Health Sciences where in 2007 she earned her Bachelor’s degree in Radiologic Sciences. She further pursued her passion for the field by acquiring a Masters in Healthcare Administration degree at Suffolk University in 2015. Her extensive experience as a Radiologic Technologist, PACS Administrator and Clinical Instructor in Radiology have supplemented her avidity for advancing patient care and quality improvement initiatives with the use of information technology, evidence-based medicine and clinical decision support.
Anna Zhao, MD
Anna Zhao received her Bachelor’s Degree in Molecular and Cellular Biology from Vanderbilt University. Currently, she is a medical student at Harvard Medical School pursuing her interest in radiology and evidence-based medicine through a research year at the Center for Evidence-Based Imaging. Her research focuses on improving quality and patient safety through analyzing IT-enabled peer learning tools, second opinion review of imaging, follow-up recommendations, and more.