Hospital-Based Medicine

Machine learning-based simulation of groundwater DIC distribution and source apportionment.

Groundwater is an important dissolved inorganic carbon (DIC)-rich reservoir and a key link connecting atmospheric, soil, rock, and surface-water carbon pools, thereby playing an important role in regional and global carbon cycling. However, systematic understanding of DIC migration and transformation mechanisms, spatial distribution patterns, and source identification in groundwater remains limite...

Machine Learning-Based Predictive Model for Functional Independence in Spinal Cord Injury: Protocol for a Predictive Rule Development and Validation Study.

BACKGROUND: Spinal cord injury (SCI) causes substantial disability by disrupting spinal pathways, making functional independence a central rehabilitation goal. In 2024, approximately 15.4 million people worldwide were living with SCI. Despite its clinical relevance, traditional prognostic tools, notably the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), ha...

Integrating Participatory Social Innovation Into Requirements Engineering for AI Health Care Solutions: Case Study.

BACKGROUND: The successful design and implementation of artificial intelligence (AI)-driven solutions in health care requires early and continuous mul...

Artificial Intelligence-Mediated Discharge Document for Accessible Health Care (AIM-HEALTH): Protocol for a Prospective, Observational, Noninterventional Study.

BACKGROUND: Hospital discharge reports (HDRs) support continuity of care; yet, their specialized terminology may hinder patient understanding and post...

Real-World Implementation of Large Language Models for Writing Clinical Discharge Summaries Within a Secure Data Environment: Development and Expert Evaluation Study.

BACKGROUND: A discharge summary should be a clinical report that documents a patient's hospital stay, including test results, diagnoses, management, a...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Refined AI-ASPECTS with modified atlas and lesion-load thresholds: advancing acute ischemic stroke imaging and prognostic prediction.

BACKGROUND: The artificial intelligence-assisted ASPECTS (AI-ASPECTS) system has become an increasingly common tool in clinical practice for assessing...

Machine Learning Prediction of Pediatric In-Hospital Survival Before Extracorporeal Membrane Oxygenation Cannulation.

Identifying suitable candidates for extracorporeal membrane oxygenation (ECMO) is still challenging. Our aim is to leverage machine learning (ML) to p...

Single-session agreement of ChatGPT and Gemini treatment recommendations with multidisciplinary tumor board decisions in thoracic oncology.

BACKGROUND: To evaluate the single-session agreement between treatment recommendations generated by ChatGPT and Gemini and real-world decisions made b...

Interpretable SHAP-based machine learning framework for patient satisfaction prediction: a case study in Thammasat University Hospital.

BACKGROUND: Patient satisfaction is a critical indicator of healthcare service quality, particularly in specialized outpatient departments where servi...

Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETCs), a CD34-positive vascular pattern in hepatocellular carcinoma (HCC), are linked to aggressive...

[Artificial intelligence-driven smart transformation of complete dentures: current status, challenges, and future prospects].

Complete denture restoration, as a major treatment for reconstructing masticatory function and restoring facial esthetics in patients with edentulism,...

Performance of the Pre-Eclampsia Integrated Estimate of Risk-Machine Learning (PIERS-ML) model in a Kenyan cohort of women with pre-eclampsia- a retrospective test derivation validation study.

OBJECTIVE: Pre-eclampsia is a cause of significant maternal morbidity and mortality, with delivery initiating resolution. The Pre-eclampsia Integrated...

Admission-Based Machine-Learning Models for Predicting Mechanical Ventilation and Mortality in Fibrotic Interstitial Lung Disease: A Multicenter Cohort Study with External Validation.

BACKGROUND: Admission-based risk stratification tools are limited for hospitalized patients with fibrotic interstitial lung disease (F-ILD). AIMS: To ...

Clinician Perspectives on Ambient AI Scribes in the Intensive Care Unit: Qualitative Interview Study.

BACKGROUND: In intensive care unit (ICU) settings, structured team-based communication, such as multidisciplinary rounds, handoffs, and goals-of-care ...

Extracting Medical Information From Unstructured Clinical Text Using Large Language Models to Enhance Health Care Interoperability: Proof-of-Concept Study.

BACKGROUND: Unstructured clinical text remains a major barrier to interoperable data reuse and large-scale secondary analysis in health care. Large la...

MDCU MedUMORE: a national digital platform for equitable and lifelong medical education in Thailand and beyond.

PROBLEM: Inequities in educational infrastructure, faculty availability, and access to continuing professional development contribute to variability i...

Multiview Laryngoscopic Image Fusion for Patient-Level Stratification of Vocal Fold Lesions.

Malignant or high-grade vocal fold disease is usually judged across repeated laryngoscopic views at different observation distances and fields of view...

Physicians and artificial intelligence diverge in evaluating large language models on real clinical cases.

While multimodal large language models (LLMs) demonstrate significant potential in healthcare applications, their clinical utility is difficult to app...

Endomyocardial Gremlin-1 is associated with structural remodeling and adverse clinical outcomes in non-ischemic cardiomyopathy.

BACKGROUND: Risk stratification in non-ischemic cardiomyopathies (NICM) remains challenging despite guideline-based phenotypic classification using mu...