Hospital-Based Medicine

Infection Control

Latest AI and machine learning research in infection control for healthcare professionals.

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COVID-19 Patients Benefitting From Remdesivir for Improved Survival: A Neural Network-Based Approach.

Conflicting results from randomized trials regarding the efficacy of remdesivir for COVID-19 have be...

A dataset and benchmark for hospital course summarization with adapted large language models.

OBJECTIVE: Brief hospital course (BHC) summaries are clinical documents that summarize a patient's h...

[Construction and preliminary validation of machine learning predictive models for cervical cancer screening based on human DNA methylation].

Using methylation characteristics of human genes to construct machine learning predictive models fo...

Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.

Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease ou...

Predicting In-Hospital Fall Risk Using Machine Learning With Real-Time Location System and Electronic Medical Records.

BACKGROUND: Hospital falls are the most prevalent and fatal event in healthcare, posing significant ...

Machine Learning in Optimising Nursing Care Delivery Models: An Empirical Analysis of Hospital Wards.

OBJECTIVE: This study aims to assess the performance of machine learning (ML) techniques in optimisi...

Improving precision instrument cleaning with a quality control module: implementation and outcomes.

OBJECTIVE: To evaluate the effectiveness of a cleaning quality control module integrated into a hosp...

Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers.

The mortality rate is very high in patients with severe COVID-19. Nearly 32% of COVID-19 patients a...

LeFood-set: Baseline performance of predicting level of leftovers food dataset in a hospital using MT learning.

Monitoring the remaining food in patients' trays is a routine activity in healthcare facilities as i...

Multimodal deep learning model for prediction of prognosis in central nervous system inflammation.

Inflammatory diseases of the CNS impose a substantial disease burden, necessitating prompt and appro...

Machine learning for early prediction of the infection in patients with urinary stone after treatment of holmium laser lithotripsy.

Patients after holmium laser lithotripsy have a certain probability of getting postoperative infecti...

Predictive Value of Machine Learning for the Risk of In-Hospital Death in Patients With Heart Failure: A Systematic Review and Meta-Analysis.

BACKGROUND: The efficiency of machine learning (ML) based predictive models in predicting in-hospita...

Evaluating the impact of an automated drug retrieval cabinet and robotic dispensing system in a large hospital central pharmacy.

PURPOSE: To determine the impact of implementing 2 technologies in succession, the Carousel system a...

Machine learning-driven in-hospital mortality prediction in HIV/AIDS patients with infection: a single-centred retrospective study.

() is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocom...

Can machine learning models improve the prediction of surgical site infection in abdominal surgery than traditional statistical models?

OBJECTIVE: To externally validate by revision and update the study on the efficacy of nosocomial inf...

Impact of wearable device data and multi-scale entropy analysis on improving hospital readmission prediction.

OBJECTIVE: Unplanned readmissions following a hospitalization remain common despite significant effo...

A Governance Framework for the Implementation and Operation of AI Applications in a University Hospital.

BACKGROUND: Artificial intelligence (AI) is becoming increasingly important in everyday life and med...

A Vision on User-Centered Implementation and Evaluation of Explainable AI for Predicting Hospital-Onset Bacteremia.

In recent years, artificial intelligence (AI) has gained momentum in many fields of daily live. In h...

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