• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.35 no.1
• /
• pp.243-272
• /
• 2024

This study was conducted with the purpose of providing suggestions for improvement through a comparison and analysis of the services of the U.S. National Library of Medicine, the world's largest medical library, and the National Center for Medical Information and Knowledge, Korea's national medical library. Core services that need to be improved are topic-specific services, community services, services by user type, educational services, technology, facility/space services, research support services, and marketing and public relations and cooperation services. Specialized libraries are also increasingly interested in topic-specific services and public services. Efficiency in access through services for each type of user is needed, and various types of educational services that do not limit the target audience are also needed. Marketing through AI, virtual reality, and technology, facility, and space services to support the disabled, research support services centered on research ethics, research grants, and programs, and collaborative services with domestic and international libraries, academic societies, institutions, and local communities in other related fields and publicity are also needed.

• Korean Journal of Radiology
• /
• v.22 no.11
• /
• pp.1743-1748
• /
• 2021

• Korean Journal of Radiology
• /
• v.23 no.12
• /
• pp.1241-1250
• /
• 2022

Objective: To conduct a simulation study to determine whether artificial intelligence (AI)-aided mammography reading can reduce unnecessary recalls while maintaining cancer detection ability in women recalled after mammography screening. Materials and Methods: A retrospective reader study was performed by screening mammographies of 793 women (mean age ± standard deviation, 50 ± 9 years) recalled to obtain supplemental mammographic views regarding screening mammography-detected abnormalities between January 2016 and December 2019 at two screening centers. Initial screening mammography examinations were interpreted by three dedicated breast radiologists sequentially, case by case, with and without AI aid, in a single session. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and recall rate for breast cancer diagnosis were obtained and compared between the two reading modes. Results: Fifty-four mammograms with cancer (35 invasive cancers and 19 ductal carcinomas in situ) and 739 mammograms with benign or negative findings were included. The reader-averaged AUC improved after AI aid, from 0.79 (95% confidence interval [CI], 0.74-0.85) to 0.89 (95% CI, 0.85-0.94) (p < 0.001). The reader-averaged specificities before and after AI aid were 41.9% (95% CI, 39.3%-44.5%) and 53.9% (95% CI, 50.9%-56.9%), respectively (p < 0.001). The reader-averaged sensitivity was not statistically different between AI-unaided and AI-aided readings: 89.5% (95% CI, 83.1%-95.9%) vs. 92.6% (95% CI, 86.2%-99.0%) (p = 0.053), although the sensitivities of the least experienced radiologists before and after AI aid were 79.6% (43 of 54 [95% CI, 66.5%-89.4%]) and 90.7% (49 of 54 [95% CI, 79.7%-96.9%]), respectively (p = 0.031). With AI aid, the reader-averaged recall rate decreased by from 60.4% (95% CI, 57.8%-62.9%) to 49.5% (95% CI, 46.5%-52.4%) (p < 0.001). Conclusion: AI-aided reading reduced the number of recalls and improved the diagnostic performance in our simulation using women initially recalled for supplemental mammographic views after mammography screening.

• Tuberculosis and Respiratory Diseases
• /
• v.42 no.2
• /
• pp.206-217
• /
• 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
• /
• v.18 no.4
• /
• pp.715-722
• /
• 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
• /
• v.1 no.1
• /
• pp.31-35
• /
• 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)
• /
• v.17 no.4
• /
• pp.1216-1233
• /
• 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.

• Journal of the Korean Society of Radiology
• /
• v.85 no.4
• /
• pp.714-726
• /
• 2024

Researchers have developed various algorithms utilizing artificial intelligence (AI) to automatically and objectively diagnose patterns and extent of pulmonary emphysema or interstitial lung diseases on chest CT scans. Studies show that AI-based quantification of emphysema on chest CT scans reveals a connection between an increase in the relative percentage of emphysema and a decline in lung function. Notably, quantifying centrilobular emphysema has proven helpful in predicting clinical symptoms or mortality rates of chronic obstructive pulmonary disease. In the context of interstitial lung diseases, AI can classify the usual interstitial pneumonia pattern on CT scans into categories like normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation. This classification accuracy is comparable to chest radiologists (70%-80%). However, the results generated by AI are influenced by factors such as scan parameters, reconstruction algorithms, radiation doses, and the training data used to develop the AI. These limitations currently restrict the widespread adoption of AI for quantifying pulmonary emphysema and interstitial lung diseases in daily clinical practice. This paper will showcase the authors' experience using AI for diagnosing and quantifying emphysema and interstitial lung diseases through case studies. We will primarily focus on the advantages and limitations of AI for these two diseases.

• The Journal of Korea Robotics Society
• /
• v.15 no.4
• /
• pp.316-322
• /
• 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
• /
• 2022.11a
• /
• pp.481-483
• /
• 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.