Infection Control

External validation of an artificial intelligence model using clinical variables, including ICD-10 codes, for predicting in-hospital mortality among trauma patients: a multicenter retrospective cohort study.

Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clinical variables to predict in-hospital mortality among trauma patients from a nationwide database. This study aimed to externally validate the performan...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of patients and their kidneys. Here, we present a case of oliguric AKI secondary to blunt trauma-induced crush syndrome complicated with severe sepsis in which the patient had a complete recovery of kidney functions after 3 months of dialysis dependency. A 40-year-old male construction worker had a sev...

Hypothesis generation for rare and undiagnosed diseases through clustering and classifying time-versioned biological ontologies.

Rare diseases affect 1-in-10 people in the United States and despite increased genetic testing, up to half never receive a diagnosis. Even when using ...

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...

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...

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...