Hospital-Based Medicine

Transforming Data from a Commercial Hospital Information System into FHIR.

The expanded use of hospital information systems in recent decades offers possibilities to use data collected in the clinical routine not only for individual patient care, but also for medical research. For this purpose, it is important use standardized formats so it can be analyzed. To achieve this goal, we brought data from the hospital information system MEONA into FHIR using the software mirth...

Detecting Adverse Drug Events in Clinical Notes Using Large Language Models.

Monitoring adverse drug events (ADEs) is critical for pharmacovigilance and patient safety. However, identifying ADEs remains challenging, as suspected or confirmed side effects are often documented solely in the unstructured text of electronic health records (EHRs). Manually reviewing clinical notes to detect ADEs is labor-intensive and time-consuming, highlighting the need for automated methods ...

Machine Learning-Based Hospital Readmission Prediction: A Comparative Analysis of Speciality-Specific vs. All-Specialities Models.

Hospital readmissions are a major challenge for healthcare systems, leading to increased costs and adverse patient outcomes. Predicting which patients...

Bridging AI and Medical Expertise: ChatGPT's Success on the Medical Specialization Residency Admission Exam in Spain.

The growing use of Artificial Intelligence (AI) in healthcare, particularly focusing on the potential of generative AI models like ChatGPT-4 is a tren...

A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions.

BACKGROUND: The rapid advancement of Artificial Intelligence (AI) has led to its widespread application across various domains, showing encouraging ou...

Boi-Ogi-To, a Traditional Japanese Kampo Medicine, Promotes Cellular Excretion of Chloride and Water by Activating Volume-Sensitive Outwardly Rectifying Anion Channels.

The Japanese Kampo medicine Boi-ogi-to (BOT) is known as an effective therapeutic agent for edema and nephrosis by promoting the excretion of excess b...

Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data.

Depression and anxiety are common comorbidities of stroke. Research has shown that about 30% of stroke survivors develop depression and about 20% deve...

Integrating Dynamic Red Blood Cell Distribution Width Monitoring and β-Blocker Therapy for Mortality Prediction in Intensive Care Unit Cardiomyopathy Patients: A Bayesian Multivariate Joint Model and Machine Learning Study.

Cardiomyopathy is a key cause of cardiovascular mortality in critically ill patients. Although red blood cell distribution width (RDW) is recognized ...

Ethics: Crisis Standards of Care Simulation.

Ethical dilemmas exist with decision-making regarding resource allocations, such as critical care, ventilators and other critical equipment, and pharm...

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 addressing the increasing complexity of oncologica...

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 and mortality, especially among patients requiring ...

Improving prediction accuracy of hospital arrival vital signs using a multi-output machine learning model: a retrospective study of JSAS-registry data.

BACKGROUND: Critically ill patients can deteriorate rapidly; therefore, prompt prehospital interventions and seamless transition to in-hospital care u...

Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study.

Atopic dermatitis is a chronic skin disease, causing itching and recurrent eczematous lesions. In Danish national register data, adults with atopic de...

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

This article describes the staged restructure of the rapid response program into a dedicated 24/7 proactive rapid response system in a quaternary acad...

Enhanced recovery programme in robotic hysterectomy.

The standard care for endometrial cancer includes total hysterectomy, bilateral salpingo-oophorectomy, peritoneal washings with or without bilateral p...

Benchmarking Ethical and Safety Risks of Healthcare LLMs in China-Toward Systemic Governance under Healthy China 2030

Large Language Models (LLMs) are poised to transform healthcare under China's Healthy China 2030 initiative, yet they introduce new ethical and pati...

Prognostic Value of the Brixia Radiological Score in COVID-19 Patients: A Retrospective Study from Romania.

The novel coronavirus pandemic, SARS-CoV-2, has a variable clinical spectrum, ranging from asymptomatic to critical forms. High mortality and morbidit...

A novel approach to cancer treatment planning using inverse sum indeg index of fuzzy graphs.

Fuzzy graph theory, with its ability to handle uncertainty and varying relationship strengths, offers a powerful tool for modeling and solving complex...

Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types.

The growing burden of cancer and recent surge in healthcare data availability call for new ways of analysing this multifactorial disease and improving...

Reasoning language models for more transparent prediction of suicide risk.

BACKGROUND: We previously demonstrated that a large language model could estimate suicide risk using hospital discharge notes.