Hospital-Based Medicine

Effect of artificial intelligence on nursing documentation and patient safety.

Nursing documentation is a fundamental component of safe clinical practice, supporting effective communication, continuity of care and patient safety. However, the increasing demands associated with electronic health records have contributed to a growing administrative workload for nurses. In response, artificial intelligence (AI) technologies are being explored as tools to support clinical docume...

Machine Learning for Evaluating the Heterogeneous Effects of Intensive In-Hospital Rehabilitation During the Postacute Phase After Hip Fracture Surgery on Activities of Daily Living.

BACKGROUND: It remains unclear which patient subgroups benefit most from intensive rehabilitation therapy. OBJECTIVES: This study aimed to examine the heterogeneity in the effects of intensive postacute rehabilitation after hip fracture surgery on activities of daily living and to identify its potential sources. RESEARCH DESIGN: A retrospective observational study. SUBJECTS: Patients aged 50 years...

Machine Learning-Guided High-Efficiency and Thermally Stable Capacitive Energy Storage in Dielectric Capacitors With a Simple Chemical Composition.

Dielectric capacitors offering ultrafast charge-discharge capability and superior reliability are essential for advanced electronic systems, but achie...

Operationalizing Digital Health Equity in Artificial Intelligence-Enabled Patient Decision Aids for Older Adults: Mixed Methods Study.

BACKGROUND: Artificial intelligence-enabled patient decision aids (AI-PDAs) hold promise for supporting older adults with chronic diseases in accessin...

Temporal deep learning for 28-day mortality prediction in critically ill ovarian cancer patients: a multicenter development and validation study using hourly vital signs.

BACKGROUND: Ovarian cancer patients requiring intensive care unit (ICU) admission face particularly grave prognosis, yet current prognostic models rel...

Natural Language Processing Improves Postoperative Discharge Instructions.

PURPOSE: To evaluate the readability, understandability, and actionability of current orthopaedic discharge instructions and assess the effectiveness ...

Identifying subgroups of ICU patients with high mortality rates using machine learning: A nationwide, population-based study.

PURPOSE: Identifying subgroups of intensive care unit (ICU) patients with high mortality rates can provide directions in policy making about appropria...

Interstitial lung disease pattern recognition on full high resolution computed tomography volume: Development and evaluation of a decision-support tool for less-experimented radiologists.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) tool to assist recognition of three major interstitial lung disease ...

White cell - platelet ratio: A strong indicator for early mortality in liver cirrhosis patients with esophagogastric varices.

Esophagogastric varices (EGV) in liver cirrhosis patients within the intensive care unit (ICU) is a significant medical concern. This study aims to de...

Predicting the flood susceptibility under land use and climate change scenarios using deep learning algorithms.

Flood risk in semi-arid, snow-fed basins is increasingly influenced by both land-use and climate change, yet their combined future effects remain poor...

Development and external validation of a machine learning prediction model for Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis in children using routine blood parameters: a retrospective cohort study.

BACKGROUND: Epstein-Barr virus (EBV) infection is a common pediatric infectious disease. Infectious mononucleosis (IM) and hemophagocytic lymphohistio...

Spatiotemporal genomic analysis and risk assessment of the plasmids carrying blaOXA-48-like genes based on a large-scale international dataset.

BACKGROUND: The spread of OXA-48-like carbapenemases represents a major public health challenge. Although previous studies have investigated OXA-48-li...

Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.

BACKGROUND: Prolonged postoperative intensive care unit (ICU) length of stay (LOS) after coronary artery bypass grafting (CABG) drives resource use ye...

Estimation of cycloplegic spherical refraction from non-cycloplegic clinical and biometric data in children using machine learning: a retrospective pilot study for screening triage.

OBJECTIVE: To develop and evaluate non-cycloplegic clinical and biometric models for estimating cycloplegic spherical power (DS), spherical equivalent...

O-RADS for assessment of adnexal lesions: current status, challenges and future directions.

The Ovarian-Adnexal Reporting and Data System (O-RADS), developed by the American College of Radiology (ACR), provides a standardized, evidence-based ...

Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.

PURPOSE: Artificial intelligence (AI) is increasingly being integrated into healthcare systems, offering new opportunities to enhance the safety, effi...

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (...

MARTP: a multi-agent simulation framework for automated radiation therapy planning based on LLMs.

Objective.High-quality radiotherapy requires accurate dose delivery to target volumes while protecting organs-at-risk. However, current clinical workf...

Identifying Unique Subgroups of Emotional and Behavioral Presentations in a Large Inpatient and Community Sample of Autistic Youth.

Autistic youth exhibit wide variability in emotional and behavioral challenges, yet few studies have identified meaningful subgroups based on these pr...

Rehabilitation technologies perceived positively by patients and facilitated intensive therapy within sessions.

BACKGROUND: Australian inpatient rehabilitation facilities are increasingly integrating rehabilitation technologies to support patient recovery. Howev...