Hospital-Based Medicine

Latest AI and machine learning research in hospital-based medicine for healthcare professionals.

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A Clinical Guideline-Grounded Hybrid Agentic Framework for Holistic Epilepsy Management.

Epilepsy is a chronic neurological disorder requiring multi-faceted management, including seizure de...

A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incompl...

A Novel Dual-Outcome Risk Calculator for Trial of Labor After Cesarean

Objective: To develop and validate a multivariable prediction model and clinically actionable risk s...

Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study

Background: The administrative burden of clinical documentation is a recognised contributor to clini...

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...

VERI-DPO: Evidence-Aware Alignment for Clinical Summarization via Claim Verification and Direct Preference Optimization

Brief Hospital Course (BHC) narratives must be clinically useful yet faithful to fragmented EHR evid...

Hospital AI and Robotics Adoption, Access Inequality, and County Mortality: A National Study Across 3,143 U.S. Counties

Hospital artificial intelligence (AI) and robotics are spreading unevenly across the United States, ...

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...

Predictors of COVID-19 hospital outcomes: a machine learning analysis of the National COVID Cohort Collaborative

Predicting hospital outcomes for patients with severe acute respiratory infections is critical for r...

Optimising antibiotic switching via forecasting of patient physiology

Timely transition from intravenous (IV) to oral antibiotic therapy shortens hospital stays, reduces ...

Characterizing Autonomic Dysfunction during Resuscitation in Sepsis using Multiscale Entropy

Rationale Autonomic dysfunction is a hallmark of sepsis pathophysiology, yet its quantification rema...

AI-Generated Responses to Patient's Messages: Effectiveness, Feasibility and Implementation

Background Generative artificial intelligence (GenAI) in healthcare may reduce administrative burden...

Multimodal EHR-Based Prediction of Pediatric Asthma Exacerbations

Pediatric asthma exacerbations are a frequent cause of emergency department (ED) visits and hospital...

Imputation of Unknown Missingness in Sparse Electronic Health Records

Machine learning holds great promise for advancing the field of medicine, with electronic health rec...

Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark

Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical predi...

Machine Intelligence-Driven Forecasting for ED Triage and Dynamic Hospital Patient Routing

Overcrowding of emergency departments (ED) is now a problem of global health care concern due to the...

Boards-style benchmarks overestimate prior-chat bias in large language models: a factorial evaluation study

Background: Large language models (LLMs) are increasingly piloted as chat interfaces for chart revie...

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