• Tuberculosis and Respiratory Diseases
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• v.42 no.2
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• pp.206-217
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• 1995

Background: In patients with obstructive sleep apnea syndrome(OSAS), there are several factors increasing upper airway resistance and there is a predisposition to compromised respiratory function during waking and sleep related to constitutional factors including a tendency to obesity. Several recent studies have suggested a possible relationship between sleep apnea(SA) and systemic hypertension. But the possible pathophysiologic link between SA and hypertension is still unclear. In this study, we have examined the relationship among age, body mass index(BMI), pulmonary function parameters and polysomnographic data in patients with OSAS. And also we tried to know the difference among these parameters between hypertensive OSAS and normotensive OSAS patients. Methods: Patients underwent a full night of polysomnography and measured pulmonary function during waking. OSAS was diagnosed if patients had more than 5 apneas per hour(apnea index, AI). A careful history of previously known or present hypertension was obtained from each patient, and patients with systolic blood pressure $\geq$ 160mmHg and/or diastolic blood pressure $\geq$ 95mmHg were classified as hypertensives. Results: The noctural nadir of arterial oxygen saturation($SaO_2$ nadir) was negatively related to AI and respiratory disturbance index(RDI), and the degree of noctural oxygen desaturation(DOD) was positively related to AI and RDI. BMI contributed to AI, RDI, $SaO_2$ nadir and DOD values. And also BMI contributed to $FEV_1,\;FEV_1/FVC$ and DLco values. There was a correlation between airway resistance(Raw) and AI, and there was a inverse correlation between DLco and DOD. But there was no difference among these parameters between hypertensive OSAS and normotensive OSAS patients. Conclusion: The obesity contributed to the compromised respiratory function and the severity of OSAS. AI and RDI were important factors in the severity of hypoxia during sleep. The measurement of pulmonary function parameters including Raw and DLco may be helpful in the prediction and assessment of OSAS patients. But we could not find clear difference between hypertensive and normotensive OSAS patients.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.715-722
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• 2023

The purpose of this study is to revitalize rehabilitation treatment for people with physical disabilities by presenting a convergence plan between e-sports and rehabilitation exercises using AI-based metaverse. Metaverse-based e-sportscan be useful in providing sports experiences to people with physical disabilities who are unable to participate in society, and this also allows individuals with disabilities to experience sports that are difficult to actually experience. The use of metaverse will enable effective rehabilitation exercise links in vulnerable communities such as hospitals and farming and fishing villages, and provide integrated services of medical and rehabilitation movements that allow exercise data to be managed in an integrated manner. To this end, interdisciplinary experts should participate in the convergence development of e-sports and rehabilitation exercise.

• Annals of Clinical Neurophysiology
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• v.1 no.1
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• pp.31-35
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• 1999

Dignosis of migraine is only based on the medical history, and objective methods to aid the clinical diagnosisare absent. Although transcranial Doppler ultrasonography (TCD) abnormalities in headache-free migraineurs have been reported previously, diagnostic criteria for migraine is still lacking and this may limit the practical application of TCD for migraine. We prospectively studied several abnormal TCD indices in interictal migraineurs and their sensitivity and specificity to define the optimal diagnostic criteria. Young (20 yrs$age=29.0{\pm}6.1yrs$) were compared to 69 controls (M:F=25:44, Mean $age=31.2{\pm}5.5yrs$). Elevated MFV (> 2SD)was observed in 63% of migraineurs while n 12% of control (p<0.01). High AI (>25%) or high HI (>3.0) was present in 17% of migraineurs, while 3% and none in controls (p<0.01). Sensitivity of elevated MFV, high AI, and high HI was 63%, 17%, 17% and specificity was 88%, 97%, 100%, respectively. If all these indices were combined, sensitivity and specificity reached 69% and 86%. These preliminary results suggest pathophysiological implication of vasospasm in interictal migraineurs, and TCD may be practically applicable for migraine. Optimal diagnostic criteria and therapeutic options for patients with abnormal TCD findings remain to bo determined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1216-1233
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• 2023

Conventional occupational therapy (OT) is conducted under the observation of an occupational therapist, and there are limitations in measuring and analyzing details such as degree of hand tremor and movement tendency, so this important information may be lost. It is therefore difficult to identify quantitative performance indicators, and the presence of observers during performance sometimes makes the subjects feel that they have to achieve good results. In this study, by using the Unity3D and artificial intelligence (AI) speaker, we propose a system that allows the subjects to steadily use it by themselves and helps the occupational therapist objectively evaluate through quantitative data. This system is based on the OT of the sensory integration approach. And the purpose of this system is to improve children's activities of daily living by providing various feedback to induce sensory integration, which allows them to develop the ability to effectively use their bodies. A dynamic OT cognitive assessment tool for children used in clinical practice was implemented in Unity3D to create an OT environment of virtual space. The Leap Motion Controller allows users to track and record hand motion data in real time. Occupational therapists can control the user's performance environment remotely by connecting Unity3D and AI speaker. The experiment with the conventional OT tool and the system we proposed was conducted. As a result, it was found that when the system was performed without an observer, users can perform spontaneously and several times feeling ease and active mind.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.316-322
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• 2020

Endoscopic spine surgery is an advanced surgical technique for spinal surgery since it minimizes skin incision, muscle damage, and blood loss compared to open surgery. It requires, however, accurate positioning of an endoscope to avoid spinal nerves and to locate the endoscope near the target disk. Before the insertion of the endoscope, a guide needle is inserted to guide it. Also, the result of the surgery highly depends on the surgeons' experience and the patients' CT or MRI images. Thus, for the training, a number of haptic simulators for spinal needle insertion have been developed. But, still, it is difficult to be used in the medical field practically because previous studies require manual segmentation of vertebrae from CT images, and interaction force between the needle and soft tissue has not been considered carefully. This paper proposes AI-based automatic vertebrae CT-image segmentation and haptic rendering method using the proposed need-tissue interaction model. For the segmentation, U-net structure was implemented and the accuracy was 93% in pixel and 88% in IoU. The needle-tissue interaction model including puncture force and friction force was implemented for haptic rendering in the proposed spinal needle insertion simulator.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.481-483
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• 2022

With the advent of the era of artificial intelligence, more and more fields have begun to use artificial intelligence technology, especially the medical field. Cancer is one of the biggest problems in the medical field. [1] If it can be detected early and treated early, the possibility of cure will be greatly increased. Malignant skin cancer, as one of the types of cancer with the highest fatality rate in recent years has problems such as relying on the experience of doctors and being unable to be detected and detected in time. Therefore, if artificial intelligence technology can be used to help doctors in early detection of skin cancer, or to allow everyone to detect skin lesions or spots anytime, anywhere, it will have great practical significance. In this paper we used attention residual learning convolutional neural network (ARL-CNN) model [2] to classify skin cancer pictures.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.183-189
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• 2023

A stroke is a medical disease where a blood vessel in the brain ruptures, causes damage to the brain. If the flow of blood and different nutrients to the brain is intermittent, symptoms may occur. Stroke is other reason for loss of life and widespread disorder. The prevalence of stroke is high in growing countries, with ischemic stroke being the high usual category. Many of the forewarning signs of stroke can be recognized the seriousness of a stroke can be reduced. Most of the earlier stroke detections and prediction models uses image examination tools like CT (Computed Tomography) scan or MRI (Magnetic Resonance Imaging) which are costly and difficult to use for actual-time recognition. Machine learning (ML) is a part of artificial intelligence (AI) that makes software applications to gain the exact accuracy to predict the end results not having to be directly involved to get the work done. In recent times ML algorithms have gained lot of attention due to their accurate results in medical fields. Hence in this work, Stroke disease identification system by using Machine Learning algorithm is presented. The ML algorithm used in this work is Artificial Neural Network (ANN). The result analysis of presented ML algorithm is compared with different ML algorithms. The performance of the presented approach is compared to find the better algorithm for stroke identification.

• Clinical Endoscopy
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• v.56 no.5
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• pp.553-562
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• 2023

Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions. Image-enhanced endoscopy (IEE) increases lesion visibility by enhancing the microstructure, blood vessels, and mucosal surface color, resulting in the detection of colorectal lesions. In recent years, various IEE techniques have been used in clinical practice, each with its unique characteristics. Numerous studies have reported the effectiveness of IEE in the detection of colorectal lesions. IEEs can be divided into two broad categories according to the nature of the image: images constructed using narrow-band wavelength light, such as narrow-band imaging and blue laser imaging/blue light imaging, or color images based on white light, such as linked color imaging, texture and color enhancement imaging, and i-scan. Conversely, artificial intelligence (AI) systems, such as computer-aided diagnosis systems, have recently been developed to assist endoscopists in detecting colorectal lesions during colonoscopy. To gain a better understanding of the features of each IEE, this review presents the effectiveness of each type of IEE and their combination with AI for colorectal lesion detection by referencing the latest research data.

• Korea Journal of Hospital Management
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• v.23 no.2
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• pp.54-66
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• 2018

Purpose: This study was to figure out relationships of perceived Technology Readiness Index(TRI), usefulness, acceptance intension, and the recognition of substitute employment of medical personnel on the artificial intelligence (AI) and internet of things (IoT) among main technologies. Methodology: To achieve the purpose, this study utilized structured survey tools to conduct a questionnaire survey of nursing, administrative and medical technology professionals at six university hospitals in Korea metropolitan area. A PLS(Partial Least Square) Path analysis was utilized To analyze the material. Findings: In the relation with the technology readiness and perceived usefulness, it had a positive influence to the perceived usefulness when the optimism and innovativeness were higher and the discomfort was lower. In the relation with the technology readiness and acceptance intension, it showed a positive influence when the innovativeness was higher and the discomfort was lower. In the relation with the perceived usefulness and acceptance intension, it had a positive influence to the acceptance intension when the perceived usefulness was higher. In the relation with the acceptance intension and the recognition of substitute employment, it showed a positive influence to the recognition of substitute employment when the acceptance intension was higher. Practical Implications: Judging based on the above study results and reference reviews, it confirmed that it is necessary to prepare in the level of hospital organization in the $4^{th}$ Industrial Revolution. They should increase the efficiency of human resources through the technological factors or changes of employment types for the additional demands of human resources to handle increasing medical demands or induce to secure necessary abilities which are changing at the right time by performing the $4^{th}$ Industrial Revolution related re-training continuously to develop the value of existing human resources.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.125-138
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• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.