Peer-reviewed papers, preprints, and conference publications.
Abstract Whole-slide images (WSIs) contain tissue information distributed across multiple magnification levels, yet most self-supervised methods treat these scales as independent views. This separation prevents models from learning representations that…
Flanagan M, Dugger B, Gutman D, Pearce T, Cooper L, Kovacs G, Fardo D, Forest S, Kukull W, Crary J, Manthey D, Biber S, Vizcarra J, Gearing M, Sargurupremraj M,…
Abstract Soft tissue tumors (STTs) pose diagnostic and therapeutic challenges due to their rarity, complexity, and morphological overlap. Accurate differentiation between benign and malignant STTs is important to set treatment…
Nash JB, Bumgardner C, Roggenkamp S, Friskney D, Armstrong S
Abstract BACKGROUND: Adherence to self-administered biologic therapies is important to induce remission and prevent adverse clinical outcomes in Inflammatory bowel disease (IBD). This study aimed to use administrative claims data…
Abstract OBJECTIVE: The objective of this study was to predict extubation readiness in preterm infants using machine learning analysis of bedside pulse oximeter and ventilator data. STUDY DESIGN: This is…
Abstract We present efforts in machine learning and time series forecasting to accurately predict counts of future suspected opioid overdoses recorded by Emergency Medical Services (EMS) in the state of…
Abstract This paper introduces an approach that combines the language reasoning capabilities of large language models (LLMs) with the benefits of local training to tackle complex language tasks. The authors…
AMIA Summits on Translational Science Proceedings (2024)
Abstract INTRODUCTION/AIMS: Muscle ultrasound has high utility in clinical practice and research; however, the main challenges are the training and time required for manual analysis to achieve objective quantification of…