Hospital-Based Medicine

Hospitalists

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

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clickBrick Prompt Engineering: Optimizing Large Language Model Performance in Clinical Psychiatry

Prompt engineering has the potential to enhance large language models’ (LLM) ability to solve tasks ...

AI-generated patient-friendly discharge summaries to empower patients

Patients often struggle to fully understand their discharge letters after inpatient hospital stays, ...

Predicting Intentional Self-Harm Following Psychiatric Discharge in Catalonia, Spain: Machine Learning Models from Linked Registry Data

Patients recently discharged from psychiatric hospitalization are at increased risk of intentional s...

Machine learning models for early prognosis prediction in cardiogenic shock

Cardiogenic shock (CS) is a severe and frequent complication of acute myocardial infarction (AMI), n...

Scalable screening for emergency department missed opportunities for diagnosis using sequential eTriggers and large language models

Missed opportunities for diagnosis (MODs), sometimes termed diagnostic errors, are a major cause of ...

Protocol for Radiographer x AI led discharge

Emergency Department (ED) overcrowding, often exacerbated by prolonged patient length of stay (LOS),...

Artificial Intelligence-assisted reader evaluation in acute CT head interpretation (AI-REACT): a multireader multicase study

Non-contrast CT head scans (NCCTH) are the most frequently requested cross-sectional imaging in the ...

Evaluating an LLM-Assisted Workflow for Clinical Documentation: A Pilot Randomized Controlled Trial on Time and Quality

Large language models (LLMs) have been investigated for clinical documentation, with concerns about ...

Machine Learning Risk Prediction for Prolonged Hospitalization in Frail Older Adults with Multimorbidity

Frailty and multimorbidity are common in older adults and contribute substantially to prolonged hosp...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evalu...

Circulating microglia-derived extracellular vesicles predict recovery after rehabilitation in stroke survivors

Timely intensive rehabilitation is crucial to contrast the negative escalation of events that follow...

Analyzing Information Disparities across Modalities in Mortality Prediction

Recent advances in deep learning have enabled the integration of heterogeneous data modalities for c...

PROGNOSTIC ACCURACY OF MACHINE LEARNING MODELS FOR IN-HOSPITAL MORTALITY AMONG CHILDREN WITH PHOENIX SEPSIS ADMITTED TO THE PEDIATRIC INTENSIVE CARE UNIT.

Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infecti...

Jan 2025 39671551
Identifying protected health information by transformers-based deep learning approach in Chinese medical text.

In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm base...

Jan 2025 39862116
Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes

Although advances in brain surgery techniques have led to fewer postoperative complications requir...

PT: A Plain Transformer is Good Hospital Readmission Predictor

Hospital readmission prediction is critical for clinical decision support, aiming to identify pati...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This rea...

Trading off performance and human oversight in algorithmic policy: evidence from Danish college admissions

Student dropout is a significant concern for educational institutions due to its social and econom...

Unlocking the Full Potential of High-Density Surface EMG: Novel Non-Invasive High-Yield Motor Unit Decomposition

The decomposition of high-density surface electromyography (HD-sEMG) signals into motor unit disch...

Automation of Trainable Datasets Generation for Medical-Specific Language Model: Using MIMIC-IV Discharge Notes.

This study introduces a novel approach for generating machine-generated instruction datasets for fin...

Aug 2024 39176825
Exploring Hospital Overcrowding with an Explainable Time-to-Event Machine Learning Approach.

Emergency department (ED) overcrowding is a complex problem that is intricately linked with the oper...

Aug 2024 39176833
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