Hospital-Based Medicine

Accuracy and empathy of AI-based conversational chatbots in response to temporomandibular dysfunction related queries.

OBJECTIVES: To compare the accuracy and empathy of responses generated by artificial intelligence (AI)-based chatbots to commonly asked temporomandibular dysfunction (TMD)-related questions. Additionally, test the performance of an automated text-based empathy detection model against subject matter experts (SMEs) judgments. MATERIALS AND METHODS: TMD-related questions (n = 14) were developed by a ...

Correlation between the high-density lipoprotein-to-low-density lipoprotein ratio and contrast-induced acute kidney injury: an analysis based on the in-hospital AKI electronic monitoring system.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common and serious complication that can occur following angiography procedures. Considering the proposed association between dyslipidemia and CI-AKI, this study aimed to investigate how the balance between the HDL-to-LDL ratio might influence the onset of CI-AKI. METHODS: From January 2019 to May 2024, patients who underwent elective ...

End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study.

BACKGROUND: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet ...

Acute deep neck infection MRI: deep learning segmentation and clinical relevance of retropharyngeal edema volume.

OBJECTIVE: Retropharyngeal edema (RPE) on MRI in patients with acute neck infection is associated with disease severity. We explored the potential rol...

Evaluation of GPT-5 for Esophageal Cancer Staging Using Fluorodeoxyglucose Positron Emission Tomography Maximum-Intensity Projection Images: Comparative Pilot Study.

BACKGROUND: Accurate esophageal cancer staging relies on 18F fluorodeoxyglucose positron emission tomography (18F FDG-PET), but its interpretation is ...

AI-Driven Patient Screening for Clinical Trials in Pancreatic Cancer: The PANCR-AI Pilot Retrospective Comparative Study.

BACKGROUND: Screening for clinical trials is challenging for clinicians due to its time-consuming and repetitive nature. The rise of artificial intell...

Predicting Geriatric Rehabilitation Stays of ≤4 Weeks After Hip Fracture Surgery: Machine Learning Approach Using Physical Activity and Patient Data.

BACKGROUND: In 2022, over 18,000 patients aged ≥70 years were hospitalized in the Netherlands for a hip fracture, with 50% requiring geriatric rehabil...

Artificial Intelligence-Enabled ECG Analysis to Predict Incident Heart Failure.

BACKGROUND: ECG-based artificial intelligence may enable efficient prediction of incident heart failure (HF) risk to facilitate preventive efforts. Pr...

Rapid response teams for new leaders: a narrative review of global evidence and implementation strategies with a focus on Japan.

BACKGROUND: Rapid response systems (RRSs) are designed to detect and treat physiological deterioration before cardiac arrest occurs. Since 2020, Japan...

The Evaluation of Transformer Models for the Detection of Adverse Drug Events: A Benchmark Study Using Dutch Free-Text Documents of Hospitalized Patients.

INTRODUCTION: Adverse drug events (ADEs) are a leading cause of preventable patient harm in hospitals. Because they are often recorded only in clinica...

Machine learning-based prediction of disability in subacute low back pain: a primary care study on clinical and psychosocial determinants.

BACKGROUND: Subacute low back pain (LBP) is a highly prevalent condition and a major contributor to disability and health care burden. Early identific...

Economic evaluations of AI applications in radiology: a systematic review.

OBJECTIVES: Artificial intelligence (AI) applications in radiology may improve clinical outcomes, but adoption is hindered by limited health economic ...

Multidimensional analysis of postoperative nursing challenges in oral cancer surgery: a retrospective study of 245 patients and proposal of the PROTECT mode.

PURPOSE: The quality of postoperative care for oral tumors critically influences patient prognosis and quality of life; however, current nursing syste...

Ensemble Machine Learning Models for Predicting Patients With High Usage: Model Validation and Economic Impact Analysis.

BACKGROUND: Machine learning models are increasingly used to predict patients at risk of high health care usage for targeted interventions. OBJECTIVE:...

Narrative as technology: the role of the medical humanities in responding to emerging biomedical technologies.

Often, the medical humanities are framed as a corrective to various instrumental inclinations within biomedicine. The humanities, according to this fo...

Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study.

OBJECTIVES: This study identifies predictors of severe COVID-19 following completion of two-dose primary series of the AZD1222 COVID-19 vaccine, emplo...

Multi-branch convolutional neural network and intracranial EEG high-frequency oscillations predict post-surgical seizure outcomes.

OBJECTIVE: Pathological High-Frequency Oscillations (HFOs) identify epileptogenic cortex, but their surgical utility is unproven. Current epilepsy sur...

AI-Augmented Mixed Reality for 3D Visualization of Perforator Vessels: A Feasibility Study in Fibular Flap Surgery.

OBJECTIVE: Using the fibular flap as a model, this study aims to develop a three-dimensional visualization method for perforator vessels. This method ...

Predicting surgical intensive care unit readmission with machine learning model: Bi-center training and validation.

BACKGROUND: Patients readmitted to the surgical intensive care unit (SICU) face a high risk of mortality and increased hospital costs. Identifying pat...

Generative AI in preanesthetic consultations: Effects on efficiency, documentation workload, quality, and physician-patient interaction: A simulation trial.

BACKGROUND: Clinicians spend over 30% of their workday on electronic health records, reducing patient interaction and contributing to burnout. Preanes...