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Hospital-Based-Medicine Subcategories: Hospitalists Infection Control Intensivists Nursing Risk Management Surveillance

Showing 1198-1218 of 4,973 articles

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia.

OBJECTIVES: Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, v...

Jun 2025 40455626

Self-supervised multi-modality learning for multi-label skin lesion classification.

BACKGROUND: The clinical diagnosis of skin lesions involves the analysis of dermoscopic and clinical...

Jun 2025 40184849

Reinforcement learning using neural networks in estimating an optimal dynamic treatment regime in patients with sepsis.

OBJECTIVE: Early fluid resuscitation is crucial in the treatment of sepsis, yet the optimal dosage r...

Jun 2025 40222267

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day...

Jun 2025 40345593

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue t...

May 2025 40446292

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the co...

May 2025 http://arxiv.org/abs/2505.23764v1

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

Multi-modal large language models have demonstrated remarkable zero-shot abilities and powerful im...

May 2025 http://arxiv.org/abs/2505.23121v1

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs

Multi-modal Large Language Models (MLLMs) excel at single-image tasks but struggle with multi-imag...

May 2025 http://arxiv.org/abs/2505.22396v1

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

Biomedical reasoning often requires traversing interconnected relationships across entities such a...

May 2025 http://arxiv.org/abs/2505.22240v2

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

Biomedical reasoning often requires traversing interconnected relationships across entities such a...

May 2025 http://arxiv.org/abs/2505.22240v1

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds

In cloud-scale systems, failures are the norm. A distributed computing cluster exhibits hundreds o...

May 2025 http://arxiv.org/abs/2506.02009v1

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning

Traditional methods of surgical decision making heavily rely on human experience and prompt action...

May 2025 http://arxiv.org/abs/2505.21596v1

Simulating Ethics: Using LLM Debate Panels to Model Deliberation on Medical Dilemmas

This paper introduces ADEPT, a system using Large Language Model (LLM) personas to simulate multi-...

May 2025 http://arxiv.org/abs/2505.21112v1

Multi-modal brain encoding models for multi-modal stimuli

Despite participants engaging in unimodal stimuli, such as watching images or silent videos, recen...

May 2025 http://arxiv.org/abs/2505.20027v1

MedDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support

Timely and personalized treatment decisions are essential across a wide range of healthcare settin...

May 2025 http://arxiv.org/abs/2505.19785v1

Task Memory Engine: Spatial Memory for Robust Multi-Step LLM Agents

Large Language Models (LLMs) falter in multi-step interactions -- often hallucinating, repeating a...

May 2025 http://arxiv.org/abs/2505.19436v1

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study.

BACKGROUND: Sepsis-associated liver injury (SALI) is a severe complication of sepsis that contribute...

May 2025 40418571

Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach.

Septic shock exhibits diverse etiologies and patient characteristics, necessitating tailored fluid m...

May 2025 40415107

Hospital-Based Medicine

Browse Categories

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia.

Self-supervised multi-modality learning for multi-label skin lesion classification.

Reinforcement learning using neural networks in estimating an optimal dynamic treatment regime in patients with sepsis.

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning

Simulating Ethics: Using LLM Debate Panels to Model Deliberation on Medical Dilemmas

Multi-modal brain encoding models for multi-modal stimuli

MedDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support

Task Memory Engine: Spatial Memory for Robust Multi-Step LLM Agents

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study.

Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach.

Multi-Person Interaction Generation from Two-Person Motion Priors

Relationship between medication regimen complexity and pharmacist engagement in fluid stewardship.

Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models

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