Surgery

Text-Attributed Knowledge Graph Enrichment with Large Language Models for Medical Concept Representation

In electronic health record (EHR) mining, learning high-quality representations of medical concepts (e.g., standardized diagnosis, medication, and procedure codes) is fundamental for downstream clinical prediction. However, robust concept representation learning is hindered by two key challenges: (i) clinically important cross-type dependencies (e.g., diagnosis-medication and medication-procedure ...

Nationwide Prediction of Missed and Cancelled Appointments Using Real-World EHR Data

ObjectivesTo develop and evaluate predictive models for unused outpatient appointments (missed or cancelled) using a large national electronic health record (EHR) repository in the United States. DesignRetrospective observational study using machine learning and statistical modeling. SettingA U.S. national electronic health record repository (Cerner Real World Database) covering healthcare encou...

LLM-Driven Target Trial Emulation with Human-in-the-Loop Validation for Randomized Trial: Automated Protocol Extraction and Real-World Outcome Evaluation{Psi}

Target trial emulation (TTE) enables causal inference from observational data but remains bottlenecked by manual, expert-dependent protocol operationa...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound...

Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models

Occlusion, where target structures are partially hidden by surgical instruments or overlapping tissues, remains a critical yet underexplored challenge...

Data-Efficient Surgical Phase Segmentation in Small-Incision Cataract Surgery: A Controlled Study of Vision Foundation Models

Surgical phase segmentation is central to computer-assisted surgery, yet robust models remain difficult to develop when labeled surgical videos are sc...

Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma

Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed a...

Benchmarking Deep Learning for Future Liver Remnant Segmentation in Colorectal Liver Metastasis

Accurate segmentation of the future liver remnant (FLR) is critical for surgical planning in colorectal liver metastases (CRLM) to prevent fatal post-...

State-Dependent Parameter Relevance in Intensive Care: Syndrome-Specific Centroids Improve Orbit-Based Mortality Prediction from AUC 0.59 to 0.83 in 59,362 Predictions

Background: The Therapeutic Distance framework (Paper 1) achieved AUC 0.61 for orbit-based mortality prediction in 11,627 sepsis patients. We hypothes...

Final Report, Center for Computer-Integrated Computer-Integrated Surgical Systems and Technology, NSF ERC Cooperative Agreement EEC9731748, Volume 1

In the last ten years, medical robotics has moved from the margins to the mainstream. Since the Engineering Research Center for Computer-Integrated Su...

Transfer Learning for Meta-analysis Under Covariate Shift

Randomized controlled trials often do not represent the populations where decisions are made, and covariate shift across studies can invalidate standa...

A Rapid Instrument Exchange System for Humanoid Robots in Minimally Invasive Surgery

Humanoid robot technologies have demonstrated immense potential for minimally invasive surgery (MIS). Unlike dedicated multi-arm surgical platforms, t...

Developmental brain age gap in prematurity and postnatally emerging delay in congenital heart disease

Brain development follows a precisely regulated biological timetable, with defined periods of vulnerability increasingly recognized in congenital diso...

Artificial Intelligence and Circulating microRNA Signatures for Early Breast Cancer Detection: A Systematic Review and Meta-Analysis

Background: Early breast cancer detection remains central to improving clinical outcomes, yet conventional screening pathways, particularly mammograph...

A Deep Learning-Based Single-View Echocardiographic Analysis for Prediction of Left Ventricular Outflow Tract Obstruction After Transcatheter Aortic Valve Replacement

Aims: Dynamic left ventricular outflow tract obstruction (LVOTO) is a hemodynamically significant complication following transcatheter aortic valve re...

Genome-Wide Variations of End Motif in Cell-Free DNA Fragments Distinguish Immunotherapy Responders from Non-Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

Reliable, minimally invasive biomarkers for predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinica...

Detection of Adversarial Attacks in Robotic Perception

Deep Neural Networks (DNNs) achieve strong performance in semantic segmentation for robotic perception but remain vulnerable to adversarial attacks, t...

A Comparative Study in Surgical AI: Datasets, Foundation Models, and Barriers to Med-AGI

Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but have lagge...

Single-Cell Analysis of Microglia and Monocyte Dynamics Uncover Distinct TNF-a-driven Neuroimmune Signatures after Intracerebral Hemorrhage

Innate immune cells contribute to both secondary brain injury and repair following intracerebral hemorrhage (ICH). However, the specific signaling pat...