- Prediction of dental caries in 12-year-old children using machine-learning algorithms
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Yang YH, Kim JS, Jeong SH
- KMID: 2471985
- J Korean Acad Oral Health.
- 2020 Mar;44(1):55-63.
- doi: 10.11149/jkaoh.2020.44.1.55
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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- Prediction of Chronic Disease-Related Inpatient Prolonged Length of Stay Using Machine Learning Algorithms
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Symum H, Zayas-Castro JL
- KMID: 2469397
- Healthc Inform Res.
- 2020 Jan;26(1):20-33.
- doi: 10.4258/hir.2020.26.1.20
OBJECTIVES: The study aimed to develop and compare predictive models based on supervised machine learning algorithms for predicting the prolonged length of stay (LOS) of hospitalized patients diagnosed with five... -
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- Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department
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Yu JY, Jeong GY, Jeong OS, Chang DK, Cha WC
- KMID: 2469396
- Healthc Inform Res.
- 2020 Jan;26(1):13-19.
- doi: 10.4258/hir.2020.26.1.13
OBJECTIVES: The aim of this study was to develop machine learning (ML) and initial nursing assessment (INA)-based emergency department (ED) triage to predict adverse clinical outcome. METHODS: The retrospective study included... -
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- First Report of Buchwaldoboletus lignicola (Boletaceae), a Potentially Endangered Basidiomycete Species, in South Korea
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Jo JW, Kwag YN, Cho SE, Han SK, Han JG, Lim YW, Sung GH, Oh SH, Kim CS
- KMID: 2470185
- Mycobiology.
- 2019 Dec;47(4):521-526.
- doi: 10.1080/12298093.2019.1682907
During the 2014 survey of the mushroom flora of Gwangneung forest in South Korea, we collected two specimens of boletoid mushroom growing on a felled tree of Pinus koraiensis. These... -
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- Effect of Acaromyces Ingoldii Secondary Metabolites on the Growth of Brown-Rot (Gloeophyllum Trabeum) and White-Rot (Trametes Versicolor) Fungi
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Olatinwo R, So CL, Eberhardt
- KMID: 2470183
- Mycobiology.
- 2019 Dec;47(4):506-511.
- doi: 10.1080/12298093.2019.1686944
We investigated the antifungal activities of an endophytic fungus identified as Acaromyces ingoldii, found on a loblolly (Pinus taeda L.) pine bolt in Louisiana during routine laboratory microbial isolations. The... -
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- A Survey of Termitomyces (Lyophyllaceae, Agaricales), Including a New Species, from a Subtropical Forest in Xishuangbanna, China
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Ye L, Karunarathna SC, Li H, Xu J, Hyde KD, Mortimer P
- KMID: 2470171
- Mycobiology.
- 2019 Dec;47(4):391-400.
- doi: 10.1080/12298093.2019.1682449
A survey of mushrooms was conducted in Xishuangbanna, Yunnan Province, China, in the rainy season (May to October) of 2012, 2013, and 2014, during which 16 specimens of Termitomyces were... -
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- Four Year Surveillance of the Vector Hard Ticks for SFTS, Ganghwa-do, Republic of Korea
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Kim-Jeon M, Jegal S, Jun H, Jung H, Park SH, Ahn SK, Lee J, Gong YW, Joo K, Kwon MJ, Roh JY, Lee WG, Bahk YY, Kim TS
- KMID: 2470003
- Korean J Parasitol.
- 2019 Dec;57(6):691-698.
- doi: 10.3347/kjp.2019.57.6.691
The seasonal abundance of hard ticks that transmit severe fever with thrombocytopenia syndrome virus was monitored with a collection trap method every April to November during 2015–2018 and with a... -
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- Machine Learning-Based Prediction of Korean Triage and Acuity Scale Level in Emergency Department Patients
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Choi SW, Ko T, Hong KJ, Kim KH
- KMID: 2462229
- Healthc Inform Res.
- 2019 Oct;25(4):305-312.
- doi: 10.4258/hir.2019.25.4.305
OBJECTIVES: Triage is a process to accurately assess and classify symptoms to identify and provide rapid treatment to patients. The Korean Triage and Acuity Scale (KTAS) is used as a... -
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- Stacking Ensemble Technique for Classifying Breast Cancer
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Kwon H, Park J, Lee Y
- KMID: 2462226
- Healthc Inform Res.
- 2019 Oct;25(4):283-288.
- doi: 10.4258/hir.2019.25.4.283
OBJECTIVES: Breast cancer is the second most common cancer among Korean women. Because breast cancer is strongly associated with negative emotional and physical changes, early detection and treatment of breast... -
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- Pullout Strength Predictor: A Machine Learning Approach
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Khatri R, Varghese V, Sharma S, Kumar GS, Chhabra HS
- KMID: 2462015
- Asian Spine J.
- 2019 Oct;13(5):842-848.
- doi: 10.31616/asj.2018.0243
STUDY DESIGN: A biomechanical study. PURPOSE: To develop a predictive model for pullout strength. OVERVIEW OF LITERATURE: Spine fusion surgeries are performed to correct joint deformities by restricting motion between two or... -
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- Antifungal Activities of Streptomyces blastmyceticus Strain 12-6 Against Plant Pathogenic Fungi
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Kim YJ, Kim JH, Rho JY
- KMID: 2470144
- Mycobiology.
- 2019 Sep;47(3):329-334.
- doi: 10.1080/12298093.2019.1635425
Streptomyces blastmyceticus strain 12-6 was isolated from a forest soil sample of Cheonan area on the basis of strong antifungal activities against plant pathogenic fungi. Butanol extracts of the cultural... -
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- Machine Learning Approaches for the Prediction of Prostate Cancer according to Age and the Prostate-Specific Antigen Level
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Lee J, Yang SW, Lee S, Hyon YK, Kim J, Jin L, Lee JY, Park JM, Ha T, Shin JH, Lim JS, Na YG, Song KH
- KMID: 2457595
- Korean J Urol Oncol.
- 2019 Aug;17(2):110-117.
- doi: 10.22465/kjuo.2019.17.2.110
PURPOSE: The aim of this study was to evaluate the applicability of machine learning methods that combine data on age and prostate-specific antigen (PSA) levels for predicting prostate cancer. MATERIALS AND... -
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- Classification of Common Relationships Based on Short Tandem Repeat Profiles Using Data Mining
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Jeong SJ, Lee HJ, Lee SD, Lee SH, Park SJ, Kim JS, Lee JW
- KMID: 2456272
- Korean J Leg Med.
- 2019 Aug;43(3):97-105.
- doi: 10.7580/kjlm.2019.43.3.97
We reviewed past studies on the identification of familial relationships using 22 short tandem repeat markers. As a result, we can obtain a high discrimination power and a relatively accurate... -
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- Detection of Suicide Attempters among Suicide Ideators Using Machine Learning
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Ryu S, Lee H, Lee DK, Kim SW, Kim CE
- KMID: 2456168
- Psychiatry Investig.
- 2019 Aug;16(8):588-593.
- doi: 10.30773/pi.2019.06.19
OBJECTIVE: We aimed to develop predictive models to identify suicide attempters among individuals with suicide ideation using a machine learning algorithm. METHODS: Among 35,116 individuals aged over 19 years from the... -
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- Perceptual and Acoustic Outcomes of Early-Stage Glottic Cancer After Laser Surgery or Radiotherapy: A Meta-Analysis
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Lee SH, Hong KH, Kim JS, Hong YT
- KMID: 2455363
- Clin Exp Otorhinolaryngol.
- 2019 Aug;12(3):241-248.
- doi: 10.21053/ceo.2018.00990
Laser surgery (LS) or radiotherapy (RT) is normally recommended in early glottic cancer. The objective of this study was to perform a comprehensive meta-analysis of acoustic and perceptual outcomes to... -
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- Prediction and Staging of Hepatic Fibrosis in Children with Hepatitis C Virus: A Machine Learning Approach
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Barakat NH, Barakat SH, Ahmed N
- KMID: 2457469
- Healthc Inform Res.
- 2019 Jul;25(3):173-181.
- doi: 10.4258/hir.2019.25.3.173
OBJECTIVES: The aim of this study is to develop an intelligent diagnostic system utilizing machine learning for data cleansing, then build an intelligent model and obtain new cutoff values for... -
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- Using big data to see the forest and the trees: endoscopic submucosal dissection of early gastric cancer in Korea
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Bang CS, Baik GH
- KMID: 2457305
- Korean J Intern Med.
- 2019 Jul;34(4):772-774.
- doi: 10.3904/kjim.2019.170
No abstract available. -
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- Effects of Outdoor Activities in Forests on Atopic Dermatitis
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Kim WK, Kim W, Woo JM
- KMID: 2455385
- Mood Emot.
- 2019 Jul;17(2):63-69.
- doi: 10.0000/me.2019.17.2.63
BACKGROUND: The aim of this study was to determine the effects of out-door activities in the forest environment, the so-called "forest therapy program," among children with atopic dermatitis (AD). METHODS: A... -
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- Development and Validation of Deep-Learning Algorithm for Electrocardiography-Based Heart Failure Identification
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Kwon JM, Kim KH, Jeon KH, Kim HM, Kim MJ, Lim SM, Song PS, Park J, Choi RK, Oh BH
- KMID: 2450395
- Korean Circ J.
- 2019 Jul;49(7):629-639.
- doi: 10.4070/kcj.2018.0446
BACKGROUND AND OBJECTIVES: Screening and early diagnosis for heart failure (HF) are critical. However, conventional screening diagnostic methods have limitations, and electrocardiography (ECG)-based HF identification may be helpful. This study... -
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- Let's Not Miss the Forest for the Trees
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Hyun SJ
- KMID: 2452653
- Neurospine.
- 2019 Jun;16(2):207-208.
- doi: 10.14245/ns.19edi.003
No abstract available. -
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