Infection Control

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study.

BACKGROUND: Home hospitalization is a care modality growing in popularity worldwide. Telemedicine-driven hospital-at-home (HAH) services could replace traditional hospital departments for selected patients. Chest x-rays typically serve as a key diagnostic tool in such cases.

JURNI (Journeying with Patients' Understanding and Responding to Needs Interactively): An In-Hospital Navigation Application for Timely Diagnosis and Treatment of Breast Cancer at the University Malaya Medical Centre.

One of the main challenges in breast cancer management is health system literacy to provide optimal and timely diagnosis and treatments within complex and multidisciplinary health system environments. Digitalised patient navigation programs have been developed and found to be helpful in high- and low-resource settings, but gaps remain in finding cost-effective navigation in the public sector in Ma...

A novel approach to antimicrobial resistance: Machine learning predictions for carbapenem-resistant Klebsiella in intensive care units.

This study was conducted at Kocaeli University Hospital in Turkey and aimed to predict carbapenem-resistant Klebsiella pneumoniae infection in intensi...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary com...

PREDICTING IN-HOSPITAL MORTALITY IN CRITICAL ORTHOPEDIC TRAUMA PATIENTS WITH SEPSIS USING MACHINE LEARNING MODELS.

Purpose: This study aims to establish and validate machine learning-based models to predict death in hospital among critical orthopedic trauma patient...

Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit (ICU) for non-neurological conditions, leading to...

Artificial intelligence-powered image analysis: A paradigm shift in infectious disease detection.

The global burden of infectious diseases significantly affects mortality rates, with their varying symptoms making it challenging to assess and determ...

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there...

Application of Raman spectroscopy and machine learning for identification and characterization.

UNLABELLED: an emerging fungal pathogen characterized by multidrug resistance and high-mortality nosocomial infections, poses a serious global health...

Empirical investigation of multi-source cross-validation in clinical ECG classification.

Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospi...

Development and validation of the PHM-CPA model to predict in-hospital mortality for cirrhotic patients with acute kidney injury.

BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis predi...

Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data.

Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, resul...

Explainable machine learning model for predicting paratracheal lymph node metastasis in cN0 papillary thyroid cancer.

Prophylactic dissection of paratracheal lymph nodes in clinically lymph node-negative (cN0) papillary thyroid carcinoma (PTC) remains controversial. T...

Development of a Surgery-specific Comorbidity Score for Use in Administrative Data.

OBJECTIVE: To create a novel comorbidity score tailored for surgical database research. BACKGROUND: Despite their use in surgical research, the Elixha...

Constructing a Hospital Department Development-Level Assessment Model: Machine Learning and Expert Consultation Approach in Complex Hospital Data Environments.

BACKGROUND: Every hospital manager aims to build harmonious, mutually beneficial, and steady-state departments. Therefore, it is important to explore ...

MAPRS: An intelligent approach for post-prescription review based on multi-label learning.

Antimicrobial resistance (AMR) is a major threat to public health worldwide. It is a promising way to improve appropriate prescription by the review a...

Preventing postoperative moderate- and high-risk pressure injuries with artificial intelligence-powered smart decompression mattress on in middle-aged and elderly patients: a retrospective cohort analysis.

Artificial intelligence technology has attained rapid development in recent years. The integration of artificial intelligence applications into press...

[Translated article] The role of artificial intelligence in scientific publishing: perspectives from hospital pharmacy.

The article examines the impact of artificial intelligence on scientific writing, with a particular focus on its application in hospital pharmacy. It ...

Application of a machine learning model for early prediction of in-hospital cardiac arrests: Retrospective observational cohort study.

OBJECTIVE: To describe the results of the application of a Machine Learning (ML) model to predict in-hospital cardiac arrests (ICA) 24 hours in advanc...

Retrospective validation study of a machine learning-based software for empirical and organism-targeted antibiotic therapy selection.

UNLABELLED: Errors in antibiotic prescriptions are frequent, often resulting from the inadequate coverage of the infection-causative microorganism. Th...