Dr. Lee is an Assistant Professor in the Division of Surgical Oncology. Her proposal is titled ‘Generating a Multimodal Machine Learning Model for Prediction of Thyroid Cancer Recurrence’. Her mentors will be: Girish Nadkarni, MD, MPH, Michael Marin, MD, and Gerald Lipshutz, MD.
Dr. Lee’s research interest focuses on optimizing methods of thyroid cancer care, specifically understanding factors that modulate the risk for thyroid cancer recurrence. After completing seven years of general surgery training and immunology research, she specialized in Endocrine Surgery by completing a year of clinical fellowship at a high-volume thyroid center. During this time, she extensively trained in the various aspects of thyroid cancer work up, diagnosis, surgical management, and surveillance. After fellowship, Dr. Lee moved to Ithaca, NY to join her husband who was on faculty at Cornell Business School. She worked at the community hospital as an attending surgeon in General Surgery where she was the only practicing Endocrine Surgeon in the county. Dr. Lee worked to expand services and continued academic pursuits by starting a Thyroid Tumor Board, supporting a multidisciplinary Thyroid Nodule Clinic, and lecturing on thyroid cancer within the hospital and community. During this time, she developed an interest in exploring the potential of applying artificial intelligence and machine learning methods to gain clinical insights from vast amounts of multimodal medical data. She has since given invited presentations at regional and local meetings on topics including Artificial Intelligence and Thyroid Cancer Care and Machine Learning Algorithms to Guide Differential Diagnosis. After being recruited back to Mount Sinai in 2021, Dr. Lee immediately resumed her academic research endeavors while building a clinical practice. She has worked to establish research projects with experts within Mount Sinai’s Biomedical Engineering and Imaging Institute, Institute for Personalized Medicine (Dr. Girish Nadkarni), the Department of Statistics at Cornell University (Dr. David Matteson), and the Department of Statistics at the University of Iowa (Dr. Andrew Thomas). Dr. Lee has also worked with colleagues at UCLA and USC to develop a multi-institution medullary thyroid cancer study. She currently serves as co-investigator on a project with Dr. William Speier from UCLA to develop and validate an extended multimodal combination convolutional neural network-graph convolutional network using ultrasound and cytopathology features of indeterminate thyroid nodules to predict malignancy. These collaborations have resulted in accepted abstracts and podium presentations at AAES and ATA on topics including generating machine learning algorithms to predict follicular thyroid carcinoma, radiomics and thyroid nodule diagnostics. Their work has been published in Surgery and JAMA Otolaryngology. Additionally, Dr. Lee has been an invited speaker to speak on artificial intelligence and the advances in thyroid cancer detection and uses in endocrine and surgical oncology.
ConduITS is supported by NCATS of the NIH’s CTSA Program. Any use of CTSA-supported resources requires citation of grant number UL1TR004419 awarded to ISMMS in the acknowledgment section of every publication resulting from this support. Adherence to the NIH Public Access Policy is also required.
