• The Korean Journal of Rehabilitation Nursing
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• v.7 no.1
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• pp.7-14
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• 2004

To examine the cognitive function of elderly, the study examined the performance of Korean normal elderly population whose age over 65 using neuropsychological instruments. It was predicted that the performance of the Korean population would be different from the U, S. mainly due to their difference in language, culture, and education. Korean elderly people from the Chungchung and Daejeon Metropolitan city(n=97) participated. Two age scores were developed: below 74 years and over 75 years. The effect of age, gender and education was examined, which yield significant age, gender and education effect. The score of DSF, DSB, TMTA, and TMTB are expected to be utilized for research purposes, such as basic, clinical, epidemiological studies, as well as practice purposes such as diagnosis and assessment of the progression of cognitive decline and dementia with MMSE-K.

• Journal of Korean Physical Therapy Science
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• v.29 no.3
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• pp.29-47
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• 2022

Purpose: This study was conducted to find out the mediated effects of smartphone overindulgence in the relationship between attention and spinal health of adolescents and to find out how cognitive strength moderates these relationships. Design: Cross-sectional study. Methods: All subjects measured attention, cognition strength, spinal angle, and smartphone overindulgence by measuring the ratio of SMR and mid-beta power to the power of the brain wave, amplitude variation of Cognitive Gamma-Peak, forward slope angle of the cervical spine, and the scale of diagnosis of smartphone addiction. Results: As a result, it shows a significant correlation between Attention, spinal angle, cognitive strength, and smartphone overindulgence(p<.05). In addition, attention was significantly mediated on the spinal angle through smartphone overindulgence(p<.001), and cognitive strength was significantly mediated in relation to smartphone overindulgence and spinal angle(p<.05). Conclusion: This result indicates that the mediation effect of overindulgence of a Smartphone is mediated according to its cognitive strength in relation to its effect of attention on the spine angle.

• School Mathematics
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• v.15 no.1
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• pp.61-75
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• 2013

This study analyzed Korean students' affective characteristics in mathematical learning according to school and sex by Factor Analysis and Cognitive Diagnosis Theory. In numerical affective achievements by Factor Analysis, there are mean differences between schools, i.e. elementary school and secondary school. And there are sexual differences within schools and boys show more positive achievement than girls. By Cognitive Diagnosis Theory, I investigated 6 affective attributes' proportions that students achieved according to school and sex. Middle school students' proportion is highest in self-control and anxiety and the attribute that students achieved most in all school is cognizing mathematical value. Boys show higher proportion in self directivity, interest and confidence than girls, but girls show higher proportion in anxiety than boys. In personal profiles, the proportion of students who achieved 5 attributes except anxiety is highest.

• Sleep Medicine and Psychophysiology
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• v.2 no.1
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• pp.44-54
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• 1995

It is very difficult to evaluate sleep disorders by simple history taking, because which covers very comprehensive areas such as psychobiosocial fields. Although polysomnography is used for the method of final diagnosis, systemic history taking and sleep question-aires are still critically important especially in evaluation of insomnia. Proper informations through sleep questionnaires can provide very precise data for effective treatment as well as exact diagnosis. Sleep questionnaires consist of largely four kinds of questionnaires, which are screening questionnaire of sleep disorders, sleep diary and questionnaire of sleep hygine, diagnostic questionnaire for specific sleep disorder and questionnaire of special symptoms of sleep disorders including insomnia, daytime sleepiness, cognitive function, mental symptom and personality, parasomnia, physical illness and sexual function. However, for more conclusive diagnosis especially in excessive daytime sleepiness nocturnal polysomnography and multiple sleep latency test should be performed.

• Journal of Oral Medicine and Pain
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• v.47 no.2
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• pp.107-108
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• 2022

Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.281-286
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• 2023

Diagnosing reading disorders involves complex procedures to evaluate complex cognitive processes. For an accurate diagnosis, a series of tests and evaluations by human experts are required. In this study, we propose a quantitative tool to diagnose reading disorders based on natural reading behaviors using minimal human input. The eye movements of the third- and fourth-grade students were recorded while they read a text at their own pace. Seven machine learning models were used to evaluate the gaze patterns of the words in the presented text and classify the students as normal or having a reading disorder. The accuracy of the machine learning-based diagnosis was measured using the diagnosis by human experts as the ground truth. The highest accuracy of 0.8 was achieved by the support vector machine and random forest classifiers. This result demonstrated that machine learning-based automated diagnosis could substitute for the traditional diagnosis of reading disorders and enable large-scale screening for students at an early age.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.164-171
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• 2021

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

• The Journal of the Korean dental association
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• v.58 no.6
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• pp.354-363
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• 2020

Patients often seek consultation with dentists for their temporomandibular disorders (TMD), especially for pain. Acute pains refer to pains that are of short duration. Common acute TMD are arthralgia and local myalgia. Diagnosis should be made based on careful history taking and clinical examination. Most acute TMD are well controlled by education, cognitive awareness training, and conservative treatment. The aggressive and irreversible treatments should not be applied. Acute TMD should be controlled in the early phase so as not to be proceed to chronic pain.

• Korean Journal of Biological Psychiatry
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• v.12 no.2
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• pp.89-97
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• 2005

Depression is a frequently developed psychiatric symptom after stroke. Poststroke depression(PSD) causes not only psychological distress related to depression but also other disturbances in many areas such as cognitive function, activities of daily living and quality of life. Therefore, a comprehensive understanding of accurate detection and appropriate treatment of depression is mandatory in patients with stroke. This review focused on the current knowledge of PSD.

• The Journal of Pediatrics of Korean Medicine
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• v.20 no.2
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• pp.147-175
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• 2006

Objective : This study is to investigate the method for assesment and diagnosis of ADHD, especially focusing on behavior rating scales. Methods : We searched the recent date of the publication and paper in ADHD. Results : For Assesment and Diagnosis of ADHD, various method such as interview with parents, child and teacher, behavior observation, behavior rating scales and neuropsychological test are used. The structured interview consists of the restrictive questions and response, and then have diagnostic algorithm, consequently can be used by untrained clinicians. Of the structured interview, standardization of K-SADS in Korean version is finished. Behavior rating scales, the form of parent, teacher and self-report questionnaires, are used as diagnosis and treatment evaluation of ADHD. Behavior rating scales consist of both ADHD-specific scales and broad-band scales designed to screen for various symptoms (including ADHD symptoms). ADHD-specific scales are useful in differential diagnosis, discrimination of subtype, treatment evaluation, However, broad-band scales are useful in preliminary examination. The neuropsychological tests can evaluate attention deficit and effect of attention deficit on cognitive function and academic performance. The neuropsychological tests also used in diagnosis and treatment evaluation of ADHD. Conclusion : For Assesment and Diagnosis of ADHD, various method are used, especially behavior rating scales are both useful and simple tool for diagnosis and treatment evaluation.