Hospital-Based Medicine

Hospitalists

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

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Propofol-associated Hypertriglyceridemia: Development and Multicenter Validation of a Machine-Learning-Based Prediction Tool.

To develop and validate an explainable machine learning (ML) tool to help clinicians predict the ris...

Impact of dielectric barrier discharge cold plasma on Dendrobium officinale polysaccharides: Physicochemical and functional properties.

Dendrobium officinale has garnered significant attention due to its notable bioactivity and health b...

Assessing artificial intelligence-generated patient discharge information for the emergency department: a pilot study.

BACKGROUND: Effective patient discharge information (PDI) in emergency departments (EDs) is vital an...

Incremental capacity analysis of battery under dynamic load conditions.

The inconsistent charge and discharge patterns of electric vehicle batteries, coupled with their ope...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic....

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases ...

Prediction of postoperative intensive care unit admission with artificial intelligence models in non-small cell lung carcinoma.

BACKGROUND: There is no standard practice for intensive care admission after non-small cell lung can...

Medical short text classification via Soft Prompt-tuning.

In recent decades, medical short texts, such as medical conversations and online medical inquiries, ...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailor...

NeuroNasal: Advanced AI-Driven Self-Supervised Learning Approach for Enhanced Sinonasal Pathology Detection.

Sinus diseases are inflammations or infections of the sinuses that significantly impact patient qual...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Early diagnosis and access to resources, support and therapy are critical for improving long-term ou...

Benchmarking of Large Language Models for the Dental Admission Test.

Large language models (LLMs) have shown promise in educational applications, but their performance ...

A comparative study of neuro-fuzzy and neural network models in predicting length of stay in university hospital.

BACKGROUND: The time a patient spends in the hospital from admission to discharge is known as the le...

Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.

BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic...

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early predicti...

Using Machine Learning to Identify Social Determinants of Health that Impact Discharge Disposition for Hospitalized Patients.

OBJECTIVE: To identify self-reported social determinants of health (SDOH) among hospitalized patient...

Using Natural Language Processing in the LACE Index Scoring Tool to Predict Unplanned Trauma and Surgical Readmissions in South Africa.

BACKGROUND: Unplanned and potentially avoidable readmission within 30 days post discharge is a major...

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