- 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
- KMID: 2429371
- J Adv Prosthodont.
- 2018 Dec;10(6):395-400.
- doi: 10.4047/jap.2018.10.6.395
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... -
- CITED
-
- Close
- SHARE
-
- Close
- Gastrointestinal polyp detection in endoscopic images using an improved feature extraction method
-
Billah M, Waheed S
- KMID: 2439535
- Biomed Eng Lett.
- 2018 Feb;8(1):69-75.
- doi: 10.1007/s13534-017-0048-x
Gastrointestinal polyps are treated as the precursors of cancer development. So, possibility of cancers can be reduced at a great extent by early detection and removal of polyps. The most... -
- CITED
-
- Close
- SHARE
-
- Close
- Application of Support Vector Machine for Prediction of Medication Adherence in Heart Failure Patients
-
Son YJ, Kim HG, Kim EH, Choi S, Lee SK
- KMID: 2284538
- Healthc Inform Res.
- 2010 Dec;16(4):253-259.
- doi: 10.4258/hir.2010.16.4.253
OBJECTIVES: Heart failure (HF) is a progressive syndrome that marks the end-stage of heart diseases, and it has a high mortality rate and significant cost burden. In particular, non-adherence of... -
- CITED
-
- Close
- SHARE
-
- Close
- Obstructive Sleep Apnea Screening Using a Piezo-Electric Sensor
-
Erdenebayar U, Park JU, Jeong P, Lee KJ
- KMID: 2377717
- J Korean Med Sci.
- 2017 Jun;32(6):893-899.
- doi: 10.3346/jkms.2017.32.6.893
In this study, we propose a novel method for obstructive sleep apnea (OSA) detection using a piezo-electric sensor. OSA is a relatively common sleep disorder. However, more than 80% of... -
- CITED
-
- Close
- SHARE
-
- Close
- Anesthesia research in the artificial intelligence era
-
Lee HC, Jung CW
- KMID: 2436031
- Anesth Pain Med.
- 2018 Jul;13(3):248-255.
- doi: 10.17085/apm.2018.13.3.248
A noteworthy change in recent medical research is the rapid increase of research using big data obtained from electrical medical records (EMR), order communication systems (OCS), and picture archiving and... -
- CITED
-
- Close
- SHARE
-
- Close
- Real-Data Comparison of Data Mining Methods in Prediction of Diabetes in Iran
-
Tapak L, Mahjub H, Hamidi O, Poorolajal J
- KMID: 2166696
- Healthc Inform Res.
- 2013 Sep;19(3):177-185.
- doi: 10.4258/hir.2013.19.3.177
OBJECTIVES: Diabetes is one of the most common non-communicable diseases in developing countries. Early screening and diagnosis play an important role in effective prevention strategies. This study compared two traditional... -
- CITED
-
- Close
- SHARE
-
- Close
- Prediction of Exposure to 1763MHz Radiofrequency Radiation Using Support Vector Machine Algorithm in Jurkat Cell Model System
-
Huang TQ, Lee MS, Bae YJ, Park HS, Park WY, Sun SJ
- KMID: 2166215
- Genomics Inform.
- 2006 Jun;4(2):71-76.
We have investigated biological responses to radiofrequency (RF) radiation in in vitro and in vivo models. By measuring the levels of heat shock proteins as well as the activation of... -
- CITED
-
- Close
- SHARE
-
- Close
- Prediction of Return-to-original-work after an Industrial Accident Using Machine Learning and Comparison of Techniques
-
Lee J, Kim HR
- KMID: 2410529
- J Korean Med Sci.
- 2018 May;33(19):e144.
- doi: 10.3346/jkms.2018.33.e144
BACKGROUND: Many studies have tried to develop predictors for return-to-work (RTW). However, since complex factors have been demonstrated to predict RTW, it is difficult to use them practically. This study... -
- CITED
-
- Close
- SHARE
-
- Close
- Detecting Manic State of Bipolar Disorder Based on Support Vector Machine and Gaussian Mixture Model Using Spontaneous Speech
-
Pan Z, Gui C, Zhang J, Zhu J, Cui D
- KMID: 2428833
- Psychiatry Investig.
- 2018 Jul;15(7):695-700.
- doi: 10.30773/pi.2017.12.15
OBJECTIVE: This study was aimed to compare the accuracy of Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) in the detection of manic state of bipolar disorders (BD) of... -
- CITED
-
- Close
- SHARE
-
- Close
- Improving the Performance of Text Categorization Models used for the Selection of High Quality Articles
-
Kim S, Choi J
- KMID: 2166614
- Healthc Inform Res.
- 2012 Mar;18(1):18-28.
- doi: 10.4258/hir.2012.18.1.18
OBJECTIVES: Machine learning systems can considerably reduce the time and effort needed by experts to perform new systematic reviews (SRs). This study investigates categorization models, which are trained on a... -
- CITED
-
- Close
- SHARE
-
- Close
- Predicting Working Memory Capacity in Older Subjects Using Quantitative Electroencephalography
-
Shin JH, Jhung K, Heo JS, An SK, Park JY
- KMID: 2419368
- Psychiatry Investig.
- 2018 Aug;15(8):790-795.
- doi: 10.30773/pi.2018.04.03.1
OBJECTIVE: We utilized a spectral and network analysis technique with an integrated support vector classification algorithm for the automated detection of cognitive capacity using resting state electroencephalogram (EEG) signals. METHODS: An... -
- CITED
-
- Close
- SHARE
-
- Close
- A Comparison of Intensive Care Unit Mortality Prediction Models through the Use of Data Mining Techniques
-
Kim S, Kim W, Park RW
- KMID: 2284550
- Healthc Inform Res.
- 2011 Dec;17(4):232-243.
- doi: 10.4258/hir.2011.17.4.232
OBJECTIVES: The intensive care environment generates a wealth of critical care data suited to developing a well-calibrated prediction tool. This study was done to develop an intensive care unit (ICU)... -
- CITED
-
- Close
- SHARE
-
- Close
- Detection of Neural Fates from Random Differentiation: Application of Support Vector MachineMin
-
Lee MS, Ahn JH, Park WY
- KMID: 2166247
- Genomics Inform.
- 2007 Mar;5(1):1-5.
Embryonic stem cells can be differentiated into various types of cells, requiring a tight regulation of transcription. Biomarkers related to each lineage of cells are used to guide the differentiation... -
- CITED
-
- Close
- SHARE
-
- Close
- Review of Machine Learning Algorithms for Diagnosing Mental Illness
-
Cho G, Yim J, Choi Y, Ko J, Lee SH
- KMID: 2447783
- Psychiatry Investig.
- 2019 Apr;16(4):262-269.
- doi: 10.30773/pi.2018.12.21.2
OBJECTIVE: Enhanced technology in computer and internet has driven scale and quality of data to be improved in various areas including healthcare sectors. Machine Learning (ML) has played a pivotal... -
- CITED
-
- Close
- SHARE
-
- Close
- Texture Analysis of Supraspinatus Ultrasound Image for Computer Aided Diagnostic System
-
Park BE, Jang WS, Yoo SK
- KMID: 2357384
- Healthc Inform Res.
- 2016 Oct;22(4):299-304.
- doi: 10.4258/hir.2016.22.4.299
OBJECTIVES: In this paper, we proposed an algorithm for recognizing a rotator cuff supraspinatus tendon tear using a texture analysis based on a histogram, gray level co-occurrence matrix (GLCM), and... -
- CITED
-
- Close
- SHARE
-
- Close
- Predictors of Medication Adherence in Elderly Patients with Chronic Diseases Using Support Vector Machine Models
-
Lee SK, Kang BY, Kim HG, Son YJ
- KMID: 2166660
- Healthc Inform Res.
- 2013 Mar;19(1):33-41.
- doi: 10.4258/hir.2013.19.1.33
OBJECTIVES: The aim of this study was to establish a prediction model of medication adherence in elderly patients with chronic diseases and to identify variables showing the highest classification accuracy... -
- CITED
-
- Close
- SHARE
-
- Close
- Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study
-
Kazemi M, Moghimbeigi A, Kiani J, Mahjub H, Faradmal J
- KMID: 2380721
- Epidemiol Health.
- 2016;38:e2016011.
- doi: 10.4178/epih.e2016011
OBJECTIVES: Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation.... -
- CITED
-
- Close
- SHARE
-
- Close
- Nomogram of Naive Bayesian Model for Recurrence Prediction of Breast Cancer
-
Kim W, Kim KS, Park RW
- KMID: 2166938
- Healthc Inform Res.
- 2016 Apr;22(2):89-94.
- doi: 10.4258/hir.2016.22.2.89
OBJECTIVES: Breast cancer has a high rate of recurrence, resulting in the need for aggressive treatment and close follow-up. However, previously established classification guidelines, based on expert panels or regression... -
- CITED
-
- Close
- SHARE
-
- Close
- Population Pharmacokinetic and Pharmacodynamic Models of Propofol in Healthy Volunteers using NONMEM and Machine Learning Methods
-
Kim YM, Kang SH, Park IS, Noh GJ
- KMID: 2211304
- J Korean Soc Med Inform.
- 2008 Jun;14(2):147-159.
OBJECTIVES: The primary objective of this study is to compare model performance of machine learning methods with that of a previous study in which a nonlinear mixed effects model was... -
- CITED
-
- Close
- SHARE
-
- Close
- Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns
-
Lee MS, Huang TQ, Seo JS, Park WY
- KMID: 2166263
- Genomics Inform.
- 2007 Sep;5(3):102-106.
Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory... -
- CITED
-
- Close
- SHARE
-
- Close
