Hospital-Based Medicine

Stigmatizing Language Detection in Opioid Use Disorder Patient-Directed Discharge Clinical Documentation: A Privacy-Preserving Analysis Using a Locally Deployed Large Language Model

Objective: Stigmatizing language in the electronic health record (EHR) has been associated with adverse patient experience in substance use disorder care, including opioid use disorder (OUD). This study evaluated a privacy-preserving, locally-deployed large language model as a method to detect stigmatizing language documentation in OUD patients with patient-directed discharge (PDD). Methods: A ret...

Operationalizing Eight-Dimensional Patient-Safety Risk Scoring at Scale: A Multi-Model Large Language Model Reliability Study

Background: Hospital incident risk scoring has long relied on two- or three-dimensional frameworks (Severity Assessment Codes or Risk Priority Numbers),even though root cause analysis standards recognize that clinical risk is multi-factorial. The obstacle has been mainly cognitive: human reviewers cannotreliably score many dimensions across high incident volumes, so richer assessmenthas not been o...

Real-world impact of a sepsis early detection model integrated into clinical workflow: a quasi-experimental study

Background: Sepsis is a life-threatening condition in which delayed recognition and treatment are associated with increased mortality. While predictiv...

Relationship Extraction for Adverse Drug Events in Clinical Notes Using Large Language Models

Background: Adverse drug events (ADEs) are a critical indicator of patient safety but are often documented only in free-text clinical notes. The poten...

Use of large language models by academic hospitalists: results of a multicenter survey

Introduction: The use of artificial intelligence (AI) by clinicians has increased rapidly in recent years, with large language models (LLMs) emerging ...

AI Adoption for NCDs in Kenya: A Qualitative Study

Background: Non-communicable diseases (NCDs) represent a critical public health challenge in Kenya, responsible for over 50% of inpatient admissions a...

Discrepancy Minimization Improves Cross-Hospital Robustness in Digital Pathology

Pathology foundation models (PFMs) have advanced rapidly in recent years and support training classifiers for a range of histopathology tasks. However...

Professionalism Pulse: Development and Validation of a Natural Language Processing Pipeline and Dashboard for Safety Culture Surveillance in NYC Health + Hospitals

Background: Professionalism and effective communication are foundational determinants of patient safety and quality of care. Unprofessional behaviors ...

A digital twin for hospital antimicrobial resistance forecasting and constrained intervention optimisation

Hospital antimicrobial resistance (AMR) emanates from an array of complex interactions between patient turnover, heterogeneous patient--staff contact ...

Post-ED Trajectory Prediction in Abdominal Pain with a Generative Medical Event Model

Importance: Abdominal pain causes roughly 10 million US emergency department (ED) visits annually, most resulting in discharge. Post-discharge courses...

Predicting Intensive Care Readmission Among Hospitalized Children

Objective: Readmissions to the PICU are associated with increased morbidity and mortality. A prediction model that can identify children at risk of re...

Clinical Note Comparison and Data Retrieval Via Embedding Vectors: Model Selection, Metrics, and Convergence

Background: Embedding models are an integral part of generative AI architectures, transforming text into embedding vectors that represent semantic con...

Large Language Model Performance in UK Advice & Guidance: A Pilot Study in Neurology

Background: Large language models (LLMs) demonstrate strong performance in controlled medical environments such as multiple choice exams, but their ut...

STOMAPY: Artificial Intelligence for Risk Stratification of Outcomes Requiring Enterostomal Therapy After Hospital Discharge Following Colorectal Surgery

Introduction: Infectious and wound-healing complications after colorectal surgery often increase the complexity of local care and the need for special...

A biologically-grounded cerebellar spiking network model with realistic synaptic transmission captures complex circuit dynamics.

Cerebellar neural circuit dynamics rely on a rich repertoire of synaptic and excitability mechanisms, which are thought to determine network computati...

RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation

Inpatient medication recommendation requires clinicians to repeatedly select specific medications, doses, and routes as a patient's condition evolves....

Improving machine learning and deep learning models for 30-day ICU readmission prediction using Ensemble Bayesian Model Averaging

Intensive Care Unit (ICU) readmissions are associated with adverse clinical outcomes and increased healthcare costs. Although existing models for pred...

Video-based Detection of Delirium in Hospitalized Adults

Delirium, a dynamic neuropsychiatric condition associated with morbidity and mortality, remains underdiagnosed due to reliance on subjective, intermit...

Causal Fairness for Survival Analysis

In the data-driven era, large-scale datasets are routinely collected and analyzed using machine learning (ML) and artificial intelligence (AI) to info...

Less is More: last observations of vital signs can outperform time series for hospital mortality prediction

Timely identification of hospital inpatients at risk of deterioration facilitates interventions to support their recovery. Many hospitals implement ea...