Hospital-Based Medicine

Tumor ablation: emerging uses, challenges, and strategic implementation. A green paper by the Network of Expertise in Cancer (JANE-2), High Tech Medical Resources, network on Physical Methods of Tumor Ablation.

The field of oncology has witnessed remarkable progress with the integration of high-tech innovations in tumor ablation. Tumor ablation therapies, such as radiofrequency ablation (RFA), microwave ablation (MWA), cryoablation (Cryo), irreversible electroporation (IRE), and electrochemotherapy (ECT) have evolved beyond conventional boundaries, offering patients less invasive, highly targeted therape...

[A two-stage model for predicting postoperative pulmonary infection in esophageal cancer patients].

Postoperative pulmonary infection (PPI) after esophageal cancer surgery occurs frequently and severely impairs patients' prognosis. Most existing prediction models cannot realize staged classification of risk factors, which limits targeted risk identification and intervention. Based on machine learning algorithms, this study integrates preoperative baseline characteristics and perioperative indica...

Using AI to identify in-hospital falls: a comparative analysis with incident reports and manual chart review.

INTRODUCTION: Falls remain a problem in hospitalised patients, especially in older adults. In-hospital falls occasionally lead to injuries. Currently,...

Advancing the Science of Surgical Education: Reflections From the 2025 University of Melbourne Department of Surgery Research Showcase.

BACKGROUND: The 2025 University of Melbourne Department of Surgery Research Showcase, held on 18 November 2025, brought together surgeons, researchers...

Risks and Benefits of Artificial Intelligence as an Adjunct in Colorectal Multidisciplinary Decision Making.

Evaluating expert decision-pattern alignment in endovascular planning for intracranial aneurysms using a multimodal large language model.

BACKGROUND: Endovascular treatment planning for intracranial aneurysms requires integrating vascular geometry, branch preservation, device feasibility...

Value operating system: a practical framework to measure outcomes-per-cost at the episode level.

OBJECTIVE: To specify a value operating system (VOS) and its executable metric-the Value Index (VI)-that expresses risk-adjusted outcomes-per-episode-...

Prediction of cardiac arrest in patients with heart failure in Sweden: a registry study with development of a machine learning model.

OBJECTIVE: 30-day survival after cardiac arrest is low, 12.4% and 36% for out-of-hospital and in-hospital cardiac arrest, respectively. Heart failure ...

Bayesian-optimized machine learning models for classifying metabolic syndrome control among NCD patients in Bangladesh hospitals.

Control of metabolic syndrome (MS) is still a major challenge for patients suffering from Non-communicable diseases (NCDs) in Bangladesh. In this stud...

Mapping the research landscape of myelodysplastic syndromes: a scientometric analysis (2014-2025).

This scientometric study critically evaluates the global evolution of myelodysplastic syndromes (MDS) research from 2014 to 2025, aiming to integrate ...

Impact of machine learning on spare parts availability for critical medical devices: a supervised machine learning perspective.

PURPOSE: This paper seeks to improve the reliability and quality of operation of the critical medical equipment methods through the combination of fai...

Early prognostication for ICU patients with combined respiratory and circulatory failure: an interpretable machine learning approach.

Accurate prognostication in the intensive care unit (ICU) is essential for delivering personalized and ethically sound care, yet it remains a challeng...

The productivity illusion: performance measurement and the invisibility of digital clinical work.

Clinical value is now produced in two distinct registers: one that requires physical presence, and one that does not. Performance measurement framewor...

Development and validation of machine-learning diagnostic models for identifying frailty in older adults with tuberculosis: a multicentre observational study protocol.

BACKGROUND: The Frailty in Tuberculosis (FIT) study aims to assess frailty in older adults with tuberculosis (TB) using machine learning (ML) to devel...

[Beyond the bladder-a specialty rediscovering itself: Outpatient. Networked. Digital].

BACKGROUND: Urology is undergoing a fundamental transformation characterized by increasing outpatient care, digitalization, and cross-sectoral network...

Right Ventricular Metrics as End Points in Clinical Trials: A Review.

IMPORTANCE: Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes an...

Advances in the management of pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs), the most common CNS tumors in children, are increasingly recognized as chronic diseases with prolonged courses an...

Prediction of Early Hospital Admission (≤24 Hours) After Stroke Using Machine Learning and Deep Learning: Multicenter Study From China.

BACKGROUND: Timely hospital admission is a prerequisite for effective acute stroke management, yet a substantial proportion of patients fail to reach ...

Patient and Facility Factors Associated with Uptake of NTAP-Billed AI to Identify Suspected LVO in Ischemic Stroke.

PURPOSE: Medicare's New Technology Add-On Payment (NTAP) incentivizes the adoption of innovative technologies. We examined factors associated with the...

CT Quantification of Intraventricular Hemorrhage Volume in Poor-Grade Aneurysmal Subarachnoid Hemorrhage: Impact on Mortality and Long-Term Disability.

BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening condition with high morbidity and mortality, particularly in poor-grade pa...