Publications (11)
EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation
Bilwaj Gaonkar, Joel Beckett, Mark Attiah +8
Translation of fully automated deep learning based medical image segmentation technologies to clinical workflows face two main algorithmic challenges. The first, is the collection…
Platform for Representation and Integration of multimodal Molecular Embeddings
Erika Yilin Zheng, Yu Yan, Baradwaj Simha Sankar +8
Existing machine learning methods for molecular (e.g., gene) embeddings are restricted to specific tasks or data modalities, limiting their effectiveness within narrow domains. As…
Silent Failures in Federated Personalization of Foundation Models
YongKyung Oh, Alex Bui
Foundation models are increasingly personalized on decentralized private data through federated learning and are now deployed at scale under growing regulatory requirements for pos…
Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?
Bilwaj Gaonkar, Matthew Edwards, Alex Bui +2
Yes, it can. Data augmentation is perhaps the oldest preprocessing step in computer vision literature. Almost every computer vision model trained on imaging data uses some form of…
Comprehensive Review of Neural Differential Equations for Time Series Analysis
YongKyung Oh, Seungsu Kam, Jonghun Lee +3
Time series modeling and analysis have become critical in various domains. Conventional methods such as RNNs and Transformers, while effective for discrete-time and regularly sampl…
Multi-View Contrastive Learning for Robust Domain Adaptation in Medical Time Series Analysis
YongKyung Oh, Alex Bui
Adapting machine learning models to medical time series across different domains remains a challenge due to complex temporal dependencies and dynamic distribution shifts. Current a…
Aztec: A Platform to Render Biomedical Software Findable, Accessible, Interoperable, and Reusable
Wei Wang, Brian Bleakley, Chelsea Ju +9
Precision medicine and health requires the characterization and phenotyping of biological systems and patient datasets using a variety of data formats. This scenario mandates the c…
Engagement Intensity as a Learner-Modeling Signal for Adaptive AI Ethics Instruction
Yongkyung Oh, Lynn Talton, Alex Bui
Adaptive AI ethics instruction in graduate research training benefits from intake measures that reflect differences in prior LLM experience. Prior coursework or workshop attendance…
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification
YongKyung Oh, Dong-Young Lim, Sungil Kim +1
Handling missing data in time series classification remains a significant challenge in various domains. Traditional methods often rely on imputation, which may introduce bias or fa…
Atherosclerosis through Hierarchical Explainable Neural Network Analysis
Irsyad Adam, Steven Swee, Erika Yilin +7
In this work, we study the problem pertaining to personalized classification of subclinical atherosclerosis by developing a hierarchical graph neural network framework to leverage…
Building an Ethical and Trustworthy Biomedical AI Ecosystem for the Translational and Clinical Integration of Foundational Models
Simha Sankar Baradwaj, Destiny Gilliland, Jack Rincon +9
Foundational Models (FMs) are gaining increasing attention in the biomedical AI ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capa…