Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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SpeciefAI: Multi-species mRNA-level Antibody Framework Generation using Transformers

Motivation: Encoding antibodies (Abs) and nanobodies (Nbs) as mRNA enables in vivo production of the...

Context-Aware Emergency Department Triage Using Pairwise Comparisons and Bradley-Terry Aggregation

Objective: To evaluate a ranking approach for emergency department (ED) waiting room prioritization ...

Federated Learning with Multi-Partner OneFlorida+ Consortium Data for Predicting Major Postoperative Complications

Background: This study aims to develop and validate federated learning models for predicting major p...

AgentTrace: Causal Graph Tracing for Root Cause Analysis in Deployed Multi-Agent Systems

As multi-agent AI systems are increasingly deployed in real-world settings - from automated customer...

Multimodal Deep Learning for Early Prediction of Patient Deterioration in the ICU: Integrating Time-Series EHR Data with Clinical Notes

Early identification of patients at risk for clinical deterioration in the intensive care unit (ICU)...

SemiTooth: a Generalizable Semi-supervised Framework for Multi-Source Tooth Segmentation

With the rapid advancement of artificial intelligence, intelligent dentistry for clinical diagnosis ...

AI-Powered Pipeline for Annotating Echocardiography Notes and Prognostic Variable Analysis in Critical Care

Abstract Background: Echocardiography (echo) notes contain valuable prognostic information for patie...

Multi-Kernel Gated Decoder Adapters for Robust Multi-Task Thyroid Ultrasound under Cross-Center Shift

Thyroid ultrasound (US) automation couples two competing requirements: global, geometry-driven reaso...

Red-Teaming Medical AI: Systematic Adversarial Evaluation of LLM Safety Guardrails in Clinical Contexts

Background: Large language models (LLMs) are increasingly deployed in medical contexts as patient-fa...

Enhanced Insights into Alcohol Use Disorder from Lifestyle, Background, and Family History in a Large-Scale Machine Learning Study

Alcohol Use Disorder (AUD) is a multifactorial condition with severe individual and societal impacts...

MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models

Safety evaluation and red-teaming of large language models remain predominantly text-centric, and ex...

LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model

Accurate classification of autonomous vehicle (AV) driving behaviors is critical for safety validati...

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

As artificial intelligence systems move toward clinical deployment, ensuring reliable prediction beh...

VGGT-Det: Mining VGGT Internal Priors for Sensor-Geometry-Free Multi-View Indoor 3D Object Detection

Current multi-view indoor 3D object detectors rely on sensor geometry that is costly to obtain (i.e....

Predicting Multi-Drug Resistance in Bacterial Isolates Through Performance Comparison and LIME-based Interpretation of Classification Models

The rise of Antimicrobial Resistance, particularly Multi-Drug Resistance (MDR), presents a critical ...

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