Hospital-Based Medicine

Development and Validation of a Machine Learning-Based Nomogram for Predicting Severe Pneumocystis jirovecii Pneumonia in Kidney Transplant Recipients.

BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in kidney transplant recipients (KTRs). Early identification of patients liable to progress to severe disease is critical for improving prognosis. This study aimed to construct and validate a machine learning-based nomogram for predicting the risk of severe PJP in KTRs using routine clinical indicators....

Data-Driven Phenotypic Clusters of Gestational Diabetes Mellitus and Associations With Risk of Perinatal Complications and Postpartum Diabetes.

OBJECTIVE: Management of gestational diabetes mellitus (GDM) largely follows a uniform approach, despite growing recognition of GDM heterogeneity. We aimed to identify data-driven GDM clusters by using machine learning techniques and clinical data and to assess their associations with perinatal complications and postpartum diabetes risk. RESEARCH DESIGN AND METHODS: In a population-based cohort st...

The Montafon proposal: New insights and emerging concepts in pulmonary rehabilitation.

Background Pulmonary rehabilitation (PR) is beneficial, yet outcome assessment remains inconsistent. A multidisciplinary D-A-CH working group reviewed...

Artificial intelligence in emergency skeletal X-ray: post-deployment monitoring and clinical impact of incorrect AI results.

OBJECTIVES: This study evaluates the impact of the artificial intelligence (AI) application BoneViewTM within a radiographer-supervised clinical workf...

Exploring pharmacy professionals insights for advancing the pharmacy curriculum: A qualitative study.

OBJECTIVE: To explore the gaps, needs, and priorities in the pharmacy curriculum of Pakistan and synthesize pharmacy professionals' perspectives to de...

Cerebrovascular CTA radiomics for objective collateral grading in acute ischemic stroke.

OBJECTIVE: Collateral circulation is a key determinant of functional outcome after large vessel occlusion (LVO) and informs thrombectomy decisions. Ho...

Current and future contributions of AI to pulmonary function test interpretation, diagnostic approaches, and predictions of disease progression.

INTRODUCTION: Artificial intelligence (AI) methods - including machine learning, deep learning, and explainable AI - are increasingly applied to pulmo...

Machine learning for predicting macrophage activation syndrome in adult patients with Still's disease.

BACKGROUND: Macrophage activation syndrome (MAS) secondary to Still's disease is a potentially fatal complication, associated with mortality rates exc...

Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients - a study based on the MIMIC-IV database.

BACKGROUND: Postoperative respiratory failure (PRF) is a severe complication after open-heart surgery, associated with increased mortality and prolong...

Predictors of weight gain in under-five children with severe acute malnutrition: A machine learning analysis of a tertiary care hospital dataset.

BACKGROUND & AIMS: Nutritionally rehabilitating children admitted to hospitals with severe acute malnutrition (SAM) and acute illness can pose signifi...

Evaluating the Performance of Large Language Models for Generating Emergency Department Discharge Instructions.

BACKGROUND: Clear discharge instructions are essential for safe emergency department (ED) care, yet creating patient-centered, health literate materia...

Enhancing hospital workforce planning, scheduling, and performance evaluation through an AI-driven human resource management system.

Efficient workforce management is critical for ensuring the quality, safety, and sustainability of hospital operations. Traditional human resource man...

Prostate MRI quality improvement: a Roadmap from the ESUR Prostate MRI Working Group.

Prostate magnetic resonance imaging (MRI) has become a crucial tool in diagnosing and managing prostate cancer, mainly by helping to avoid unnecessary...

Accurate, fair, and generalisable scaling of injury severity score-based AI with demographics in terms of mortality in patients with trauma: multi-centre, multi-national retrospective cohort study.

BACKGROUND: Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma...

Predicting infarct outcomes after extended time window thrombectomy in large vessel occlusion using knowledge guided deep learning.

BACKGROUND: Predicting the final infarct after an extended time window mechanical thrombectomy (MT) is beneficial for treatment planning in acute isch...

Prediction of favorable outcomes of acute basilar artery occlusion using machine learning.

BACKGROUND: This study aims to develop an interpretable machine learning model using SHapley Additive exPlanations (SHAP) to predict favorable outcome...

Forecasting emergency department visits in the reference hospital of the Balearic Islands: The role of tourist and weather data.

Accurate forecasting of patient arrivals at emergency departments (EDs) is vital for efficient resource allocation and high-quality patient care. In t...

Development and temporal validation of an interpretable point score for in-hospital mortality in CLL/SLL using the U.S. National Inpatient Sample, 2016-2022.

In-hospital mortality among patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) is ∼6%, yet no validated, transparent beds...

The Quality of Artificial Intelligence Chatbot Responses to Patient Questions on Surgical Infection Prevention.

BACKGROUND: As patients increasingly turn to artificial intelligence (AI) chatbots for medical information, concerns remain regarding the accuracy, tr...

A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-chain Disruption.

Cold-chain disruptions during storage and distribution of raw poultry can significantly reduce product shelf-life and safety. This study evaluated the...