- A prediction model for adolescents’ skipping breakfast using the CART algorithm for decision trees: 7th (2016–2018) Korea National Health and Nutrition Examination Survey
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Choi SA, Chung SS, Rho JO
- KMID: 2544286
- J Nutr Health.
- 2023 Jun;56(3):300-314.
- doi: 10.4163/jnh.2023.56.3.300
Purpose This study sought to predict the reasons for skipping breakfast by adolescents aged 13–18 years using the 7th Korea National Health and Nutrition Examination Survey (KNHANES). Methods The participants included 1,024 adolescents.... -
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- A machine learning based decision tree analysis of influential factor for the number of remaining teeth in Korean adults
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Hwang SY, Park JE
- KMID: 2541088
- J Korean Acad Oral Health.
- 2023 Mar;47(1):26-31.
- doi: 10.11149/jkaoh.2023.47.1.26
Objectives: This study aims to investigate the effect of determinants on the number of remaining teeth in Korean adults using a machine learning-based decision tree analysis. Methods: The study used data... -
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- The identification of high-risk groups for long-term care insurance: A retrospective study using national health insurance service database
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Song MK, Park YW, Han EJ
- KMID: 2540625
- J Korean Gerontol Nurs.
- 2023 Feb;25(1):44-55.
- doi: 10.17079/jkgn.2023.25.1.44
Purpose: This study aimed to identify high-risk groups for Long-Term Care Insurance (LTCI) in older people not approved for LTCI and to examine the characteristics of each high-risk group. Methods: This... -
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- Machine learning for the prediction of preclinical airway management in injured patients: a registry-based trial
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Luckscheiter A, Zink W, Lohs T, Eisenberger J, Thiel M, Viergutz T
- KMID: 2538023
- Clin Exp Emerg Med.
- 2022 Dec;9(4):304-313.
- doi: 10.15441/ceem.22.335
Objective The aim of this study was to determine the feasibility of using machine learning to establish the need for preclinical airway management for injured patients based on a standardized... -
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- A model for predicting fall experience in the elderly population over 65 years old: Decision tree analysis
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Han M
- KMID: 2540612
- J Korean Gerontol Nurs.
- 2022 Nov;24(4):366-376.
- doi: 10.17079/jkgn.2022.24.4.366
Purpose: This study aimed to construct a model to predict whether the elderly population over 65 years of age will experience falls according to multi-drug therapy and related factors. Methods:... -
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- The Primary Process and Key Concepts of Economic Evaluation in Healthcare
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Kim Y, Kim Y, Lee HJ, Lee S, Park SY, Oh SH, Jang S, Lee T, Ahn J, Shin S
- KMID: 2534250
- J Prev Med Public Health.
- 2022 Sep;55(5):415-423.
- doi: 10.3961/jpmph.22.195
Economic evaluations in the healthcare are used to assess economic efficiency of pharmaceuticals and medical interventions such as diagnoses and medical procedures. This study introduces the main concepts of economic... -
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- Cost-Effectiveness Analysis of Home-Based Hospice-Palliative Care for Terminal Cancer Patients
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Kim Ys, Han E, Lee Jw, Kang HT
- KMID: 2530414
- Korean J Hosp Palliat Care.
- 2022 Jun;25(2):76-84.
- doi: 10.14475/jhpc.2022.25.2.76
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
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Del Real A, Del Real O, Sardina S, Oyonarte R
- KMID: 2527454
- Korean J Orthod.
- 2022 Mar;52(2):102-111.
- doi: 10.4041/kjod.2022.52.2.102
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
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Odukoya O, Nwaneri S, Odeniyi I, Akodu B, Oluwole E, Olorunfemi G, Popoola O, Osuntoki A
- KMID: 2526494
- Healthc Inform Res.
- 2022 Jan;28(1):58-67.
- doi: 10.4258/hir.2022.28.1.58
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
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Lee HJ, Na II, Kang KA
- KMID: 2519877
- Korean J Hosp Palliat Care.
- 2021 Sep;24(3):184-193.
- doi: 10.14475/jhpc.2021.24.3.184
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
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Shim SS, Lee SH, Lee JB, Seo YE, Lee HJ
- KMID: 2519855
- J Korean Neuropsychiatr Assoc.
- 2021 Aug;60(3):204-212.
- doi: 10.4306/jknpa.2021.60.3.204
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
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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
- KMID: 2515850
- Gut Liver.
- 2021 May;15(3):459-465.
- doi: 10.5009/gnl19304
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)
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Kim HS, Jeong SH
- KMID: 2513539
- J Korean Biol Nurs Sci.
- 2021 Feb;23(1):31-42.
- doi: 10.7586/jkbns.2021.23.1.31
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
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Lee Y, Kim H, Lee Y, Jeong H
- KMID: 2513455
- J Korean Acad Nurs.
- 2021 Feb;51(1):40-53.
- doi: 10.4040/jkan.20207
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
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Seo I
- KMID: 2512145
- J Bacteriol Virol.
- 2020 Dec;50(4):257-262.
- doi: 10.4167/jbv.2020.50.4.257
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
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Chong Y, Lee JY, Kim Y, Choi J, Yu H, Park G, Cho MY, Thakur N
- KMID: 2509499
- J Pathol Transl Med.
- 2020 Nov;54(6):462-470.
- doi: 10.4132/jptm.2020.07.11
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
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Karajizadeh M, Nasiri M, Yadollahi M, Zolfaghari AH, Pakdam A
- KMID: 2508620
- Healthc Inform Res.
- 2020 Oct;26(4):284-294.
- doi: 10.4258/hir.2020.26.4.284
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
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Shin SH
- KMID: 2508238
- J Korean Acad Nurs.
- 2020 Oct;50(5):686-698.
- doi: 10.4040/jkan.20044
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
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Kim BR, Kim M, Choi CW, Cho S, Youn SW
- KMID: 2504861
- Ann Dermatol.
- 2020 Aug;32(4):298-305.
- doi: 10.5021/ad.2020.32.4.298
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
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Park H, Ha J
- KMID: 2500600
- J Korean Acad Nurs.
- 2020 Apr;50(2):191-199.
- doi: 10.4040/jkan.2020.50.2.191
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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