• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.138-146
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• 2024

Purpose To evaluate whether the image quality of chest radiographs obtained using a camera-type portable X-ray device is appropriate for clinical practice by comparing them with traditional mobile digital X-ray devices. Materials and Methods Eighty-six patients who visited our emergency department and underwent endotracheal intubation, central venous catheterization, or nasogastric tube insertion were included in the study. Two radiologists scored images captured with traditional mobile devices before insertion and those captured with camera-type devices after insertion. Identification of the inserted instruments was evaluated on a 5-point scale, and the overall image quality was evaluated on a total of 20 points scale. Results The identification score of the instruments was 4.67 ± 0.71. The overall image quality score was 19.70 ± 0.72 and 15.02 ± 3.31 (p < 0.001) for the mobile and camera-type devices, respectively. The scores of the camera-type device were significantly lower than those of the mobile device in terms of the detailed items of respiratory motion artifacts, trachea and bronchus, pulmonary vessels, posterior cardiac blood vessels, thoracic intervertebral disc space, subdiaphragmatic vessels, and diaphragm (p = 0.013 for the item of diaphragm, p < 0.001 for the other detailed items). Conclusion Although caution is required for general diagnostic purposes as image quality degrades, a camera-type device can be used to evaluate the inserted instruments in chest radiographs.

• Journal of the Korean Society of Radiology
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• v.83 no.1
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• pp.112-126
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• 2022

Purpose To determine the value of 3 Tesla (T) MRI texture analysis for predicting tumor margin infiltration in soft tissue sarcomas. Materials and Methods Thirty-one patients who underwent 3T MRI and had a pathologically confirmed diagnosis of soft tissue sarcoma were included in this study. Margin infiltration on pathology was used as the gold standard. Texture analysis of soft tissue sarcomas was performed on axial T1-weighted images (WI) and T2WI, fat-suppressed contrast-enhanced (CE) T1WI, diffusion-weighted images (DWI) with b-value of 800 s/mm², and apparent diffusion coefficient (ADC) was mapped. Quantitative parameters were compared between sarcomas with infiltrative margins and those with circumscribed margins. Results Among the 31 patients with soft tissue sarcomas, 23 showed tumor margin infiltration on pathology. There were significant differences in kurtosis with the spatial scaling factor (SSF) of 0 and 6 on T1WI, kurtosis (SSF, 0) on CE-T1WI, skewness (SSF, 0) on DWI, and skewness (SSF, 2, 4) on ADC between sarcomas with infiltrative margins and those with circumscribed margins (p ≤ 0.046). The area under the receiver operating characteristic curve based on MR texture features for identification of infiltrative tumor margins was 0.951 (p < 0.001). Conclusion MR texture analysis is reliable and accurate for the prediction of infiltrative margins of soft tissue sarcomas.

• Journal of the Korean Society of Radiology
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• v.83 no.1
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• pp.149-161
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• 2022

Purpose To investigate the correlation between computer-aided diagnosis (CAD) parameters in 3-tesla (T) MRI and pathologic immunohistochemical (IHC) markers in invasive carcinoma of no special type (NST). Materials and Methods A total of 94 female who were diagnosed with NST carcinoma and underwent 3T MRI using CAD, from January 2018 to April 2019, were included. The relationship between angiovolume, curve peak, and early and late profiles of dynamic enhancement from CAD with pathologic IHC markers and molecular subtypes were retrospectively investigated using Dwass, Steel, Critchlow-Fligner multiple comparison analysis, and univariate binary logistic regression analysis. Results In NST carcinoma, a higher angiovolume was observed in tumors of higher nuclear and histologic grades and in lymph node (LN) (+), estrogen receptor (ER) (-), progesterone receptor (PR) (-), human epidermal growth factor 2 (HER2) (+), and Ki-67 (+) tumors. A high rate of delayed washout and a low rate of delayed persistence were observed in Ki-67 (+) tumors. In the binary logistic regression analysis of NST carcinoma, a high angiovolume was significantly associated with a high nuclear and histologic grade, LN (+), ER (-), PR (-), HER2 (+) status, and non-luminal subtypes. A high rate of washout and a low rate of persistence were also significantly correlated with the Ki-67 (+) status. Conclusion Angiovolume and delayed washout/persistent rate from CAD parameters in contrast enhanced breast MRI correlated with predictive IHC markers. These results suggest that CAD parameters could be used as clinical prognostic, predictive factors.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.185-196
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• 2023

Purpose This study aimed to investigate radiomics analysis of ultrasonographic images to develop a potential biomarker for predicting lymph node metastasis in papillary thyroid carcinoma (PTC) patients. Materials and Methods This study included 431 PTC patients from August 2013 to May 2014 and classified them into the training and validation sets. A total of 730 radiomics features, including texture matrices of gray-level co-occurrence matrix and gray-level run-length matrix and single-level discrete two-dimensional wavelet transform and other functions, were obtained. The least absolute shrinkage and selection operator method was used for selecting the most predictive features in the training data set. Results Lymph node metastasis was associated with the radiomics score (p < 0.001). It was also associated with other clinical variables such as young age (p = 0.007) and large tumor size (p = 0.007). The area under the receiver operating characteristic curve was 0.687 (95% confidence interval: 0.616-0.759) for the training set and 0.650 (95% confidence interval: 0.575-0.726) for the validation set. Conclusion This study showed the potential of ultrasonography-based radiomics to predict cervical lymph node metastasis in patients with PTC; thus, ultrasonography-based radiomics can act as a biomarker for PTC.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.638-652
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• 2023

Purpose To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method. Materials and Methods This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity. Results The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.53-68
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• 2024

Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

• The Journal of Korean Academy of Sensory Integration
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• v.22 no.1
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• pp.1-14
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• 2024

Objective : This study aimed to investigate the impact of Ayres' sensory integration (ASI) intervention on motor skills and occupational participation of preschool children with attention-deficit/hyperactivity disorder (ADHD). Method : Children with ADHD aged between 4 and 6 years who met the inclusion and exclusion criteria were randomly recruited through screening tests. The subjects were divided into an experimental group (10 subjects) and a control group (8 subjects). The instruments used were the Bruininks-Oseretsky test of motor proficiency-2 (BOT-2), Pediatric Evaluation of Disability Inventory (PEDI), and Goal Attainment Scale (GAS) to evaluate occupational participation. The subjects in the experimental group underwent individual sensory integration therapy according to the ASI principles for 40 minutes twice a week in a total of 16 sessions over eight weeks. The control group did not receive the ASI intervention. Data analysis was performed using the Mann-Whitney U test, chi-squared test, Wilcoxon signed-rank test, and Cohen's d test in SPSS 20.0. Results : The ASI experimental group had significantly higher scores in total motor composite, manual coordination, body coordination, strength, and agility in motor function than the control group (p<.05). The two groups did not differ significantly in terms of occupational participation (PEDI), but GAS scores for individual target activities were significantly higher in the experimental group than in the control group (p<.05). Conclusion : This study shows that the ASI intervention has positive effects on motor skills and occupation participation among preschool children with ADHD.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.54-62
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• 2024

SICM (Scanning Ion Conductivity Microscopy) is a technique for measuring surface topography in an environment where electrochemical reactions occur, by detecting changes in ion conductivity as a nanopipette tip approaches the sample. This study includes an investigation of the current response curve, known as the approach curve, according to the distance between the tip and the sample. First, a simulation analysis was conducted on the approach curves. Based on the simulation results, then, several measuring experiments were conducted concurrently to analyze the difference between the simulated and measured approach curves. The simulation analysis confirms that the current squeezing effect occurs as the distance between the tip and the sample approaches half the inner radius of the tip. However, through the calculations, the decrease in current density due to the simple reduction in ion channels was found to be much smaller compared to the current squeezing effect measured through actual experiments. This suggests that ion conductivity in nano-scale narrow channels does not simply follow the Nernst-Einstein relationship based on the diffusion coefficients, but also takes into account the fluidic hydrodynamic resistance at the interface created by the tip and the sample. It is expected that SICM can be combined with SECM (Scanning Electrochemical Microscopy) to overcome the limitations of SECM through consecutive measurement of the two techniques, thereby to strengthen the analysis of electrochemical surface reactivity. This could potentially provide groundbreaking help in understanding the local catalytic reactions in electroless plating and the behaviors of organic additives in electroplating for various kinds of patterns used in semiconductor damascene processes and packaging processes.