Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.
Myung Hwan Lee;Eun-Kyung Kim;Eun Ju Lee;Ha Yan Kim;Jung Hyun Yoon
Journal of the Korean Society of Radiology
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v.81
no.1
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pp.157-165
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2020
Purpose To evaluate the optimal measurement location, cut-off value, and diagnostic performance of S-Shearwave in differential diagnosis of breast masses seen on ultrasonography (US). Materials and Methods During the study period, 225 breast masses in 197 women were included. S-Shearwave measurements were made by applying a square region-of-interest automatically generated by the US machine. Shearwave elasticity was measured three times at four different locations of the mass, and the highest shearwave elasticity was used for calculating the optimal cut-off value. Diagnostic performance was evaluated by using the area under the receiving operator characteristic curve (AUC). Results Of the 225 breast masses, 156 (69.3%) were benign and 69 (30.7%) were malignant. Mean S-Shearwave values were significantly higher for malignant masses (108.0 ± 70.0 kPa vs. 43.4 ± 38.3 kPa; p < 0.001). No significant differences were seen among AUC values at different measurement locations. With a cut-off value of 41.9 kPa, S-Shearwave showed 85.7% sensitivity, 63.9% specificity, 70.7% accuracy, and positive and negative predictive values of 51.7% and 90.8%, respectively. The AUCs for US and S-Shearwave did not show significant differences (p = 0.179). Conclusion S-Shearwave shows comparable diagnostic performance to that of grayscale US that can be applied for differential diagnosis of breast masses seen on US.
This research aims to investigate methods of leveraging generative artificial intelligence in service sectors where consumer sentiment and experience are paramount, focusing on minimizing hallucination phenomena during usage and developing strategic services tailored to consumer sentiment and experiences. To this end, the study examined both mechanical approaches and user-generated prompts, experimenting with factors such as business item definition, provision of persona characteristics, examples and context-specific imperative verbs, and the specification of output formats and tone concepts. The research explores how generative AI can contribute to enhancing the accuracy of personalized content and user satisfaction. Moreover, these approaches play a crucial role in addressing issues related to hallucination phenomena that may arise when applying generative AI in real services, contributing to consumer service innovation through generative AI. The findings demonstrate the significant role generative AI can play in richly interpreting consumer sentiment and experiences, broadening the potential for application across various industry sectors and suggesting new directions for consumer sentiment and experience strategies beyond technological advancements. However, as this research is based on the relatively novel field of generative AI technology, there are many areas where it falls short. Future studies need to explore the generalizability of research factors and the conditional effects in more diverse industrial settings. Additionally, with the rapid advancement of AI technology, continuous research into new forms of hallucination symptoms and the development of new strategies to address them will be necessary.
Jung Hee Hong;Eun-Ah Park;Whal Lee;Chulkyun Ahn;Jong-Hyo Kim
Korean Journal of Radiology
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v.21
no.10
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pp.1165-1177
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2020
Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.
Journal of Korean Home Economics Education Association
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v.35
no.4
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pp.1-12
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2023
At a time when interest in the educational use of ChatGPT is increasing, it is necessary to investigate the perception of ChatGPT among college students. A survey was conducted to compare the current status of internet and interactive artificial intelligence use and perceptions of ChatGPT after using it in the following courses in Spring 2023; 'Family Life and Culture', 'Fashion and Museums', and 'Fashion in Movies' in the first semester of 2023. We also looked at comparative analysis reports and reflection diaries. Information for coursework was mainly obtained through internet searches and articles, but only 9.84% used interactive AI, showing that its application to learning is still insufficient. ChatGPT was first used in the Spring semester of 2023, and ChatGPT was mainly used among conversational AI. ChatGPT is a bit lacking in terms of information accuracy and reliability, but it is convenient because it allows students to find information while interacting easily and quickly, and the satisfaction level was high, so there was a willingness to use ChatGPT more actively in the future. Regarding the impact of ChatGPT on education, students said that it was positive that they were self-directed and that they set up a cooperative class process to verify information through group discussions and problem-solving attitudes through questions. However, problems were recognized that lowered trust, such as plagiarism, copyright, data bias, lack of up-to-date data learning, and generation of inaccurate or incorrect information, which need to be improved.
PET (positron emission tomography) permits the investigation of physiological and biochemical processes in vivo. The accuracy of quantifying PET data is affected by its finite spatial resolution, which causes partial volume effects. In this study, we developed a method for partial volume correction using Hoffman phantom PET and MR data, and applied various FWHM (full width at half maximum) levels. We also applied this method to PET images of normal controls and tested for the possibility of clinical application. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices. The gray matter and white matter regions were then segmented into binary images. Each binary image was convolved by 4, 8, 12, 16 mm FWHM levels. These convolved images of gray and white matter were merged corresponding to the same level of FWHM. The original PET images were then divided by the convolved binary images voxel-by-voxel. These corrected PET images were multiplied by binary images. The corrected PET images were evaluated by analyzing regions of interests, which were drawn on the gray and white matter regions of the original MR image slices. We calculated the ratio of white to gray matter. We also applied this method to the PET images of normal controls. On analyzing the corrected PET images of Hoffman phantom, the ratios of the corrected images increased more than that of the uncorrected images. With the normal controls, the ratio of the corrected images increased more than that of the uncorrected images. The ratio increase of the corrected PET images was lower than that of the corrected phantom PET images. In conclusion, the method developed for partial volume correction in PET data may be clinically applied, although further study may be required for optimal correction.
Jo, Jung Hun;Kim, Byeong Jin;Roh, Shi Won;Lee, Hyeon Chan;Jang, Hyeong Jun;Kim, Hoi Nam;Song, Jae Hun;Kim, Young Jae
The Journal of Korean Society for Radiation Therapy
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v.25
no.1
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pp.33-40
/
2013
Purpose: The purpose of this study was to evaluate the possibility to optimize the gated treatment delivery time and maintenance of stable respiratory by the introduction of breath with the assistance of auditory-visual-tactile sense. Materials and Methods: The experimenter's respiration were measured by ANZAI 4D system. We obtained natural breathing signal, monitor-induced breathing signal, monitor & ventilator-induced breathing signal, and breath-hold signal using real time monitor during 10 minutes beam-on-time. In order to check the stability of respiratory signals distributed in each group were compared with means, standard deviation, variation value, beam_time of the respiratory signal. Results: The stability of each respiratory was measured in consideration of deviation change studied in each respiratory time lapse. As a result of an analysis of respiratory signal, all experimenters has showed that breathing signal used both Real time monitor and Ventilator was the most stable and shortest time. Conclusion: In this study, it was evaluated that respiratory gated radiation therapy with auditory-visual-tactual sense and without auditory-visual-tactual sense feedback. The study showed that respiratory gated radiation therapy delivery time could significantly be improved by the application of video feedback when this is combined with audio-tactual sense assistance. This delivery technique did prove its feasibility to limit the tumor motion during treatment delivery for all patients to a defined value while maintaining the accuracy and proved the applicability of the technique in a conventional clinical schedule.
Surfactant-aided in situ soil flushing has been proposed as an alternative for the expensive and time consuming 'pump and treat' technology in remediation of contaminated soil and groundwater Injected surfactants can effectively solubilize contaminants sorbed to the soil matrix or nonaqueous phase liquids(NAPLs) in residual saturation. The contaminants solubilized in groundwater are recovered and treated further. The theoretical background of the technology and the results of the field operations, mostly in the US. were summarized. In addition, the factors crucial to the successful application of the technology were discussed. Cost analyses and technical limitations in current applications were also discussed. In conclusion, it is likely that in situ surfactant flushing become a viable option for soil remediation in limited cases. Currently, further advances with respect to operation cost and to treatment efficiency are required for more extensive application of the technology. However, the current trends in soil remediation, specially the growing emphasis on risk based corrective action and natural attenuation, will increase the competitiveness of the technology. For example, removal of easily washable contaminants by short term soil flushing followed by long term monitoring and natural attenuation can greatly reduce the operation cost and time.
Journal of the Korean Association of Oral and Maxillofacial Surgeons
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v.27
no.3
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pp.214-220
/
2001
The clinical application of the three-dimensional radiographic technique had been limited to standard Broadbent-Bolton cephalometer with biplanar stereoradiography. We developed a new method for compensating the error of head position in ordinary non-biplanar cephalostat. It became to possible to use the three dimensional cephalogram commonly in clinical bases. 1. The method of methemetical compensation of head positioning error in non-biplanar condition was evaluated with dry skull. The error of the method of first and the second trial was $0.46{\pm}1.21$, $0.33{\pm}0.90mm$, which means the error of the head positioning correction in conventional cephalogram was within clinical acceptance. 2. The reproducibility of this system for clinical application was 0.54 mm ($-2.99{\sim}2.26mm$) which defines the absolute mean difference of the first and second trial. Compare to the The landmark identification error $1.2{\pm}1.6mm$, the error of the measurement was within the range of landmark identification error. The result indicates the adequate clinical accuracy of the computation of three-dimensional coordinates by compensation of the error of the head position in ordinary non-biplanar cephalostat.
Kim, Jong-Sik;Jung, Chun-Young;Oh, Dong-Gyoon;Song, Ki-Won;Park, Young-Hwan
The Journal of Korean Society for Radiation Therapy
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v.18
no.1
/
pp.13-19
/
2006
Purpose: To evaluate whether modified MUPIT applicator can effectively eradicate recurrent tumor in uterine cervix cancer and reduce rectal complication after complete radiation treatment. Materials and Methods: Modified MUPIT applicator basically consists of an acrylic cylinder with flexible brain applicator, an acrylic template with a predrilled array of holes that serve as guides for interstitial needles and interstitial needles. CT scan was peformed to determine tumor volume and the position of interstitial needles. Modified MUPIT applicator was applied to patient in operation room and the accuracy for position of interstitial needles in tumor volume was confirmed by CTscan. Brachytherapy was delivered using modified MUPIT applicator and RALS(192-lr HDR) after calculated computer planning by orthogonal film. The daily dose was 600cGy and the total dose was delivered 3,000 cGy in tumor volume by BID. Rectal dose was measured by TLD at 5 points so that evaluated the risk of rectal complication. Results: The application of modified MUPIT applicator improved dramatically dose distributions in tumor volume and follow-up of 3 month for this patient was clinically partial response without normal tissue complication, Rectal dose was measured 34.1 cGy, 57.1 cGy, 103.8 cGy, 162.7 cGy, 165.7 cGy at each points, especially the rectal dose including previous EBRT and ICR was 34.1 cGy, 57.1 cGy. Conclusion: Patients with locally recurrent tumor in uterine cervix cancel treated with modified MUPIT applicator can expect reasonable rates of local control. The advantages of the system are the fixed geometry provided by the template and cylinders. and improved dose distributions in irregular tumor volume without rectal complication.
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