Hospital-Based Medicine

RIPTOSO: The development of a screening tool for adverse events during forensic-psychiatric inpatient treatments of offenders with schizophrenia spectrum disorders.

Adverse events such as compulsory measures, absconding, illicit substance use, self-harm, aggressive...

ChatGPT-4 vs. multi-disciplinary tumor board decisions for the therapeutic management of primary laryngeal cancer.

BACKGROUND: Artificial intelligence-based clinical decision support systems are promising tools for ...

Predicting prolonged length of in-hospital stay in patients with non-ST elevation myocardial infarction (NSTEMI) using artificial intelligence.

BACKGROUND: Patients presenting with non-ST elevation myocardial infarction (NSTEMI) are typically e...

Recent Advances in Fe-Free M-N-C Catalysts for Oxygen Reduction Reaction.

Atomically dispersed metal-nitrogen-carbon (M-N-C) materials, characterized by well-defined coordina...

Patient prioritization for pharmaceutical intervention in the hospital setting: a retrospective cross-sectional study.

OBJECTIVES: Prioritization of patients requiring pharmaceutical intervention is critical given limit...

Severe community-acquired pneumonia (sCAP): advances in management and future directions.

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity a...

Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning.

The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with...

Potential role of large language models and personalized medicine to innovate cardiac rehabilitation.

Cardiac rehabilitation is a crucial multidisciplinary approach to improve patient outcomes. There is...

Evaluating the Prognostic Value of Kansas City Cardiomyopathy Questionnaire (KCCQ) Scores for 6-Month Readmissions in Southeast Asian Populations With Heart Failure.

BACKGROUND: Heart failure (HF) is a prevalent cause of hospital readmissions. Our study aims to dete...

Machine learning approaches for predicting prolonged hospital length of stay after lumbar fusion surgery in patients aged 75 years and older: a retrospective cohort study based on comprehensive geriatric assessment.

OBJECTIVE: Postoperative recovery following lumbar fusion surgery in patients aged 75 years and olde...

Current State of Fibrotic Interstitial Lung Disease Imaging.

Interstitial lung disease (ILD) diagnosis is complex, continuously evolving, and increasingly relian...

Approaches for Measuring and Predicting Fouling During Thermal Processing of Dairy Solutions.

Fouling during the thermal processing of dairy products remains a significant challenge, reducing op...

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data.

Acute Respiratory Distress Syndrome (ARDS), characterized by the rapid onset of respiratory failure ...

Insights into suspended sediment and microplastic budget of a lowland river: integrating in-situ measurements, Sentinel-2 imagery, and machine learning.

The calculations on fluvial microplastic load (MPL) provide dynamic and actionable metrics for under...

Medical physicists at the forefront of multidisciplinary AI integration in healthcare.

Machine Learning-Based Prediction to Support ICU Admission Decision Making among Very Old Patients with Respiratory Infections: A Proof of Concept on a Nationwide Population-Based Cohort Study.

BackgroundIntensive care unit (ICU) hospitalizations of very old patients with acute respiratory inf...

[Rethinking scientific integrity in plastic surgery: Reflections on editorial and institutional responsibilities].

Plastic surgery, by nature an innovative discipline, has historically relied on clinical case report...

Emerging Technology and the Future of Perioperative Care: Perspectives and Recommendations From the 2023 Stoelting Conference of the Anesthesia Patient Safety Foundation.

Anesthesiology has a longstanding commitment to patient safety, characterized by innovative research...

A comprehensive review of ICU readmission prediction models: From statistical methods to deep learning approaches.

The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to...

Healing with hierarchy: Hierarchical attention empowered graph neural networks for predictive analysis in medical data.

In healthcare, predictive analysis using unstructured medical data is crucial for gaining insights i...

Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy.

BACKGROUND: Takotsubo cardiomyopathy (TC) is an acute heart failure syndrome characterized by transi...