Hospital-Based Medicine

Hospitalists

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

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Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

Identification of the neuron type is critical when using extracellular recordings in awake, behaving...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a c...

Partial vs. Corona Discharges in XLPE-Covered Conductors: High-Resolution Antenna Dataset for ML Applications.

Accurate differentiation between partial discharges (PD) and corona discharges in XLPE-covered condu...

Development and Pilot Testing of an Artificial Intelligence and Care Coach Intervention for Cognitively Impaired Older Adults.

BACKGROUND: Care transitions from the emergency department (ED) to community settings are particular...

Hydraulic Performance Modeling of Inclined Double Cutoff Walls Beneath Hydraulic Structures Using Optimized Ensemble Machine Learning.

This study investigates the effectiveness of inclined double cutoff walls installed beneath hydrauli...

Who Knows Anatomy Best? A Comparative Study of ChatGPT-4o, DeepSeek, Gemini, and Claude.

This study evaluates the performance of ChatGPT-4o (OpenAI), DeepSeek-v3 (DeepSeek), Gemini 2.0 (Goo...

Improving Large Language Models' Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation.

BACKGROUND: The American Medical Association recommends that electronic health record (EHR) notes, o...

Designing Pb-Free High-Entropy Relaxor Ferroelectrics with Machine Learning Assistance for High Energy Storage.

High-entropy tactics present exceptional promise in advancing the dielectric energy storage of relax...

Machine learning based prediction of MnO cathode discharge capacity for high-performance zinc-ion batteries.

Zinc-ion batteries (ZIBs) are considered as a cheaper, non-toxic and safer alternative to lithium-io...

Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units.

This study aims to establish and validate prediction models based on novel machine learning (ML) alg...

A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean.

Arctic rivers deliver 11% of the global river discharge volume into the Arctic Ocean, influencing oc...

Research on multi-branch residual connection spectrum image classification based on attention mechanism.

The acoustic spectrogram arranges the frequencies in the sound along the frequency spread, and trans...

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors ...

Machine learning approaches for predicting heart failure readmissions.

PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelih...

Clinical decision support using pseudo-notes from multiple streams of EHR data.

Electronic health records (EHR) contain data from disparate sources, spanning various biological and...

Development of a machine learning model to identify the predictors of the neonatal intensive care unit admission.

Scientists aim to create a system that can predict the likelihood of newborns being admitted to the ...

Machine learning to improve predictive performance of prehospital early warning scores.

Early warning scores are used to assess acute patients' risk of being in a critical situation, allow...

[Early warning scores: a rapid umbrella review].

BACKGROUND: Early warning scores (EWS) are used for monitoring and evaluating vital signs in hospita...

A comparative study of recent large language models on generating hospital discharge summaries for lung cancer patients.

OBJECTIVE: Generating discharge summaries is a crucial yet time-consuming task in clinical practice,...

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