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Cost-Effectiveness Analysis of Home-Based Hospice-Palliative Care for Terminal Cancer Patients

Kim Ys, Han E, Lee Jw, Kang HT

Purpose: We compared cost-effectiveness parameters between inpatient and homebased hospice-palliative care services for terminal cancer patients in Korea. Methods: A decision-analytic Markov model was used to compare the cost-effectiveness of...
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Use of automated artificial intelligence to predict the need for orthodontic extractions

Del Real A, Del Real O, Sardina S, Oyonarte R

Objective: To develop and explore the usefulness of an artificial intelligence system for the prediction of the need for dental extractions during orthodontic treatments based on gender, model variables, and...
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Development and Comparison of Three Data Models for Predicting Diabetes Mellitus Using Risk Factors in a Nigerian Population

Odukoya O, Nwaneri S, Odeniyi I, Akodu B, Oluwole E, Olorunfemi G, Popoola O, Osuntoki A

Objectives: This study developed and compared the performance of three widely used predictive models—logistic regression (LR), artificial neural network (ANN), and decision tree (DT)—to predict diabetes mellitus using the socio-demographic,...
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Decision Tree Model for Predicting Hospice Palliative Care Use in Terminal Cancer Patients

Lee HJ, Na II, Kang KA

Purpose: This study attempted to develop clinical guidelines to help patients use hospice and palliative care (HPC) at an appropriate time after writing physician orders for lifesustaining treatment (POLST) by...
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A Study on the Relationship Between Mental Health Variables and Physical Activity Variables in the Clinical Group of North Korean Defectors: A Pilot Study

Shim SS, Lee SH, Lee JB, Seo YE, Lee HJ

Objectives This study is designed to extract a representative variable that distinguishes psychiatric patients of North Korean Defectors and a control group by using machine learning based on measured mental...
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Difficult Biliary Cannulation from the Perspective of PostEndoscopic Retrograde Cholangiopancreatography Pancreatitis: Identifying the Optimal Timing for the Rescue Cannulation Technique

Lee YS, Cho CM, Cho KB, Heo J, Jung MK, Kim SB, Kim KH, Kim TN, Lee DW, Han J, Kim HG, Kim D, Kim H

Background/Aims: Recently, the European Society of Gastrointestinal Endoscopy (ESGE) proposed criteria for “difficult biliary cannulation” during endoscopic retrograde cholangiopancreatography (ERCP). This study aimed to investigate the clinical relevance of the...
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Identification of Subgroups with Poor Glycemic Control among Patients with Type 2 Diabetes Mellitus: Based on the Korean National Health and Nutrition Examination Survey from KNHANES VII (2016 to 2018)

Kim HS, Jeong SH

Purpose: This study was performed to assess the level of blood glucose and to identify poor glycemic control groups among patients with type 2 diabetes mellitus (DM). Methods: Data of...
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Comparison of the Prediction Model of Adolescents’ Suicide Attempt Using Logistic Regression and Decision Tree: Secondary Data Analysis of the 2019 Youth Health Risk Behavior Web-Based Survey

Lee Y, Kim H, Lee Y, Jeong H

Purpose: The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. Methods: This study...
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Predictions of Sampling Site Based on Microbial Compositions Using a Decision Tree-based Method

Seo I

The nose and throat are sites commonly used to obtain swab specimens to diagnose upper respiratory tract infections, and some studies have shown differences between the diagnostic accuracies of nose...
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A machine-learning expert-supporting system for diagnosis prediction of lymphoid neoplasms using a probabilistic decision-tree algorithm and immunohistochemistry profile database

Chong Y, Lee JY, Kim Y, Choi J, Yu H, Park G, Cho MY, Thakur N

Background: Immunohistochemistry (IHC) has played an essential role in the diagnosis of hematolymphoid neoplasms. However, IHC interpretations can be challenging in daily practice, and exponentially expanding volumes of IHC data...
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Mortality Prediction from Hospital-Acquired Infections in Trauma Patients Using an Unbalanced Dataset

Karajizadeh M, Nasiri M, Yadollahi M, Zolfaghari AH, Pakdam A

Objectives: Machine learning has been widely used to predict diseases, and it is used to derive impressive knowledge in the healthcare domain. Our objective was to predict in-hospital mortality from...
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Analysis of Subgroups with Lower Level of Patient Safety Perceptions Using Decision-Tree Analysis

Shin SH

Purpose: This study was aimed to investigate experiences, perceptions, and educational needs related to patient safety and the factors affecting these perceptions. Methods: Study design was a descriptive survey conducted...
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Predictive Model for Differential Diagnosis of Inflammatory Papular Dermatoses of the Face

Kim BR, Kim M, Choi CW, Cho S, Youn SW

Background: The clinical features of inflammatory papulardermatoses of the face are very similar. Their clinical manifestationshave been described on the basis of a small numberof case reports and are not...
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Prediction Models of Mild Cognitive Impairment Using the Korea Longitudinal Study of Ageing

Park H, Ha J

Purpose: The purpose of this study was to compare sociodemographic characteristics of a normal cognitive group and mild cognitive impairment group, and establish prediction models of Mild Cognitive Impairment (MCI)....
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Prediction of dental caries in 12-year-old children using machine-learning algorithms

Yang YH, Kim JS, Jeong SH

OBJECTIVES: The decayed-missing-filled (DMFT) index is a representative oral health indicator. Prediction of DMFT index is an important basis for the development of public oral health care projects and strategies...
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Evaluation of Food Labeling Policy in Korea: Analyzing the Community Health Survey 2014–2017

Jo HS, Jung SM

BACKGROUND: As Koreans adopt more Westernized diets, consumer demands for processed food products are growing. The Korean government implemented a food labeling system to help people reasonably choose processed foods....
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Identification of High-risk Groups of Suicide from the Depressed Elderly using Decision Tree Analysis

Hong S, Lee D

PURPOSE: The aim of this study is to explore levels of suicidal ideation and identify subgroups of high suicidal risk among the depressed elderly in Korea. METHODS: A descriptive cross-sectional design...
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A Prediction Model of Factors related to Career Maturity in Korean High School Students

Seo J, Kim M

PURPOSE: The purpose of this study was to identify factors associated with career maturity among Korean high school students. METHODS: A descriptive cross-sectional design was adopted using secondary data from the...
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Machine-Learning Based Automatic and Real-time Detection of Mouse Scratching Behaviors

Park I, Lee K, Bishayee K, Jeon HJ, Lee H, Lee U

Scratching is a main behavioral response accompanied by acute and chronic itch conditions, and has been quantified as an objective correlate to assess itch in studies using laboratory animals. Scratching...
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A pilot study using machine learning methods about factors influencing prognosis of dental implants

Ha SR, Park HS, Kim EH, Kim HK, Yang JY, Heo J, Yeo IS

PURPOSE: This study tried to find the most significant factors predicting implant prognosis using machine learning methods. MATERIALS AND METHODS: The data used in this study was based on a systematic...
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