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Healthcare Informatics Research
Scopus
ISSN 2093-3681 · The Korean Society of Medical Informatics · 750 artikel di indeks
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Artikel Jurnal Teks lengkap
Legal Barriers to Implementing AI-Enabled Emergency Medical Services in Korea: Focus on the Medical Service Act, Emergency Medical Service Act, and Personal Information Protection Act
Objectives In prehospital and in-hospital emergency care, artificial intelligence (AI)-enabled emergency medical services (EMS) systems are reshaping clinical workflows through real-time triage, automated hospital assignment, telemedicine, and biometric monitoring. However, their implementation in…
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Artikel Jurnal Teks lengkap
Machine Learning–Based Classification of Active and Latent Phases of Inherited Retinal Dystrophies Using Synthetic Proteomic Data: A Pathway-Based Application Exercise
Objectives Inherited retinal dystrophies are characterized by high genetic and phenotypic heterogeneity, and their clinical progression may alternate between latent and active phases. Identifying the onset of the active phase may support earlier intervention for inflammatory retinal degeneration…
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Early Detection of Parkinson’s Disease Using Automatic Classification of Single-photon Emission Computed Tomography Images
Objectives Parkinson’s disease (PD) is a chronic neurodegenerative disorder characterized by central nervous system dysfunction. Early identification may enable prompt treatment and help slow the progression of disabling symptoms. Previous studies have reported that clinical assessments based on…
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Artikel Jurnal Teks lengkap
Machine Learning Techniques to Predict Fetal Nutritional Status
Objectives Malnutrition remains the leading cause of child mortality in Tanzania, with over 34% of children under 5 years of age affected by stunting and approximately 5% experiencing acute malnutrition. This study aimed to develop a machine learning model to predict fetal nutritional status using…
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From Operating System to Operating Society: The Next Mission of Medical Informatics
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Artikel Jurnal Teks lengkap
Evaluation and Comparison of Machine Learning Methods for Type 2 Diabetes Classification and Associated Factors
Objectives Type 2 diabetes mellitus (T2DM) is a prevalent chronic metabolic disorder associated with serious complications, including nephropathy, cardiovascular disease, retinopathy, and neuropathy. Given its increasing incidence and the complexity of associated factors—such as obesity, metabolic…
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Artikel Jurnal Teks lengkap
Development and Evaluation of a Custom GPT-Based Artificial Intelligence Clinical Decision Support System for Emergency Department Interdepartmental Consultation Automation
Objectives This study aimed to develop a custom GPT-based, knowledge-guided documentation support system that drafts emergency department (ED) interdepartmental consultation requests from minimal free-text input and evaluate its feasibility, usability, and workflow integration. Methods The system…
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Prediction of Postoperative Length of Stay in Patients with Hip Fracture: A Two-Stage Machine Learning Approach
Objectives This study aimed to apply machine learning (ML) techniques to predict postoperative length of stay (LOS) in patients with hip fracture. Because LOS varies widely across individuals owing to complex clinical factors, accurate prediction remains challenging. To address this challenge, an…
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De-Identification of Magnetic Resonance Imaging to Protect Patient Privacy in Research Use: A Comprehensive Review
Objectives Brain magnetic resonance imaging (MRI) contains identifiable facial and cranial features, creating privacy risks that can limit secondary research use. This review examines current MRI de-identification technologies, quantitative validation methods, and governance frameworks to identify…
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Comparative Analysis of Regularised Logistic Regression and Random Forest Models for In-hospital or 30-day Post-Discharge Mortality Prediction within the Hospital Standardised Mortality Ratio Framework
Objectives The hospital standardised mortality ratio (HSMR) is the ratio of the observed number of hospital deaths to the expected number of deaths, with the latter estimated using statistical models that adjust for available case-mix factors. This study aimed to develop and validate in-hospital or…
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Artikel Jurnal Teks lengkap
Application of Machine Learning Algorithms for Predicting Infant Mortality in India: An Analysis of the National Family Health Survey-5, 2019–2021
Objectives Machine learning (ML) techniques have shown strong potential for predicting infant mortality (IM), but their application in the Indian context remains limited. This study aimed to use ML algorithms to predict IM in India using a large national survey database. Methods Data were analyzed…
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Artificial Intelligence Exhibits Critical Blind Spots in Allergy Test Room Safety Design
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Development and Evaluation of BABAT TB: A Smart System-Based Reminder Box for Enhancing Tuberculosis Medication Adherence
Objectives This study aimed to develop and evaluate the functionality of a smart system-based prototype, “BABAT TB,” a medication box designed to assist tuberculosis (TB) patients in adhering to their treatment schedules. Methods The development of the BABAT TB prototype followed the Design Science…
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Construction and Application of a Biological Sample Library Information Management System Based on a Data Governance System in China
Objectives This study aimed to develop and implement a hospital-based Biobank Information Management System (Version 1.0) within a structured data governance framework, and to evaluate its effectiveness in improving standardized biospecimen management, operational efficiency, and research support…
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Engaging with Facebook Health Support Groups among Australian Culturally and Linguistically Diverse Populations
Objectives This study aims to explore the key factors that enhance engagement in Facebook health support groups among Australian culturally and linguistically diverse (CALD) communities. Methods A cross-sectional online survey was conducted using convenience sampling. A total of 1,145 CALD…
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Artikel Jurnal Teks lengkap
Maternal Coffee Consumption during Pregnancy and Risk of Allergic Diseases in Children: The Korean Children’s Environmental Health Study
Objectives The effects of maternal coffee consumption during pregnancy on childhood allergic diseases (ADs) remain insufficiently established. This study aimed to investigate the association between maternal coffee consumption during pregnancy and the risk of ADs in offspring up to 36 months of…
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Educational Needs and Level of Knowledge in Standard Healthcare Terminology Use in Korea: A Cross-Sectional Survey
Objectives This study aimed to investigate the experience, knowledge, and educational needs regarding standard healthcare terminologies—specifically Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and the International…
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Nurses’ Perceptions and Utilization Plans for Applying Companion Robots to Acute Stroke Patient Care: A Delphi Study
Objectives This study aimed to explore nurses’ perceptions of, and utilization plans for, companion robots to support the physical and mental health of patients with acute stroke. In addition, the study sought to provide foundational data for the development of companion robots tailored to acute…
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Artikel Jurnal Teks lengkap
Survival Period Prediction in Cervical Cancer Patients Using the Selective Stacking Technique
Objectives This study aims to increase the effectiveness of cervical cancer treatment by developing a survival prediction model using an innovative ensemble machine learning approach, namely the selective stacking technique. Methods Patient data obtained from the Faculty of Medicine, Chiang Mai…
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Artikel Jurnal Teks lengkap
Machine Learning for Predicting Coronary Heart Disease Risk in Patients with Hypertension: An Ensemble Modeling Approach
Objectives This study aimed to develop an optimized ensemble learning model to improve the prediction of hypertension complicated by coronary heart disease (CHD) through advanced feature selection and classifier fusion, thereby enhancing both accuracy and stability in risk assessment. Methods We…