Hospital-Based Medicine

Systematic Exploration of Hospital Cost Variability: A Conformal Prediction-Based Outlier Detection Method for Electronic Health Records.

Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. Traditional methods like Diagnosis-Related Groups (DRGs) aid in cost management but lack practical solutions for enhancing hospital care value. We introduce a novel methodology for outlier detection in Electronic Health Records (EHRs) using Conformal ...

A Mortality Risk Prediction Model for Septic Shock in Patients Aged ≥50: Role of Norepinephrine Index and Procalcitonin.

BACKGROUND: Septic shock is a high-mortality syndrome, particularly in patients aged 50 and older. Predicting mortality in this population is challenging due to clinical heterogeneity and limitations of traditional scoring systems like SOFA and APACHE II. This study aimed to develop and validate a predictive model using norepinephrine index (NEI)-a novel biomarker defined as the norepinephrine dos...

A Machine Learning Model to Predict Treatment Effect Associated with Targeted Temperature Management After Cardiac Arrest.

BACKGROUND: Targeted temperature management (TTM) has been associated with neurological recovery among comatose survivors of cardiac arrest. The aim o...

Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial.

BACKGROUND: Early diagnosis of low ejection fraction (EF) remains challenging despite being a treatable condition. This study aimed to evaluate the ef...

Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example.

Continuous Emission Monitoring Systems (CEMS) are critical for real-time pollutant measurement, widely deployed to supervise industrial emissions and ...

Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography (CAIFE), an international multicentre multidisciplinary study.

INTRODUCTION: Congenital heart defect (CHD) is a significant, rapidly emerging global problem in child health and a leading cause of neonatal and chil...

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the ris...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and earl...

Ethical Considerations for Generative Artificial Intelligence in Plastic Surgery.

The integration of artificial intelligence (AI) into surgical care is rapidly transforming healthcare by enhancing efficiency, clinical decision-makin...

Machine learning models for forecasting microplastic dynamics in China's coastal waters.

Understanding spatial-temporal microplastic (MP) patterns and regional drivers in China's coastal waters is crucial for pollution interventions. Based...

A NOVEL MACHINE LEARNING APPROACH FOR TUMOR DETECTION BASED ON TELOMERIC SIGNATURES.

Cancer remains one of the most complex diseases faced by humanity, with over 200 distinct types, each characterized by unique molecular profiles that ...

Large Language Models in Medicine: Applications, Challenges, and Future Directions.

In recent years, large language models (LLMs) represented by GPT-4 have developed rapidly and performed well in various natural language processing ta...

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 coordination structures, have emerged as promising candida...

Experience of Cardiovascular and Cerebrovascular Disease Surgery Patients: Sentiment Analysis Using the Korean Bidirectional Encoder Representations from Transformers (KoBERT) Model.

BACKGROUND: Cardiovascular and cerebrovascular diseases significantly contribute to global mortality and disability. The shift to outpatient postopera...

From Fragile Lives to Forensic Truth: Multimodal Forensic Approaches to Pediatric Homicide and Suspect Death.

Forensic investigation of child homicides presents unique challenges due to the vulnerability of children and the complexity of distinguishing betwee...

Editorial: Current status of neural networks that subserve emotion and cognition - unraveling the complex brain through multidisciplinary contributions in awake brain surgery.

A Novel and Modern Calculator to Predict Vaginal Birth after Cesarean Delivery.

Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach....

The use of imaging in the diagnosis and treatment of thromboembolic pulmonary hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a potentially life-threatening condition, classified as group 4 pulmonary hypertension (PH), ...

Evaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations.

BACKGROUND: Hospital discharge summaries are essential for the continuity of care. However, medical jargon, abbreviations, and technical language ofte...

What are we learning with Yoga? Mapping the scientific literature on Yoga using a vector-text-mining approach.

The techniques used in yoga have roots in traditions that precede modern science. Research shows that yoga enhances quality of life and well-being, po...