• Clinical Endoscopy
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• v.57 no.1
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• pp.18-23
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• 2024

Computer-assisted polyp characterization (computer-aided diagnosis, CADx) facilitates optical diagnosis during colonoscopy. Several studies have demonstrated high sensitivity and specificity of CADx tools in identifying neoplastic changes in colorectal polyps. To implement CADx tools in colonoscopy, there is a need to confirm whether these tools satisfy the threshold levels that are required to introduce optical diagnosis strategies such as "diagnose-and-leave," "resect-and-discard" or "DISCARD-lite." In this article, we review the available data from prospective trials regarding the effect of multiple CADx tools and discuss whether they meet these thresholds.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.465-468
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• 1997

A Study on Computer Assisted Diagnosis (CAD) system extract ing lung cancer part from Digital X-ray Computerized Tomography(CT) image is discussed in this paper. It is very crucial to segment the image of lung into the three organ area such as inside, outside and the hilum so that the variant image processing algorithm can be applied an each area respectively. In this paper, the efficient algorithm extracting lung cancer part is proposed with characterizing lung hilum part and its associated vessel patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.595-617
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• 2010

This paper proposes a novel of a personalized Computer Assisted Language Learning (CALL) system based on learner's cognitive abilities related to foreign language proficiency. In this CALL system, a strategy of retrieval learning, a method of learning memory cycle, and a method of repeated learning are applied for effective vocabulary memorization. The system is designed to offer personalized learning based on cognitive abilities related to the human language process. For this, the proposed CALL system has a cognitive diagnosis module which can measure five types of cognitive abilities. The results of this diagnosis are used to create dynamic learning scenarios for personalized learning and to evaluate user performance in the learning. This system is also designed in order to have users be able to create learning word lists and to share them simply with various functions based on open APIs. Additionally, through experiments, it has shown that this system helps students to learn English vocabulary effectively and enhances their foreign language skills.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.410-427
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• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.

• Clinical Endoscopy
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• v.57 no.3
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• pp.302-308
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• 2024

With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.58-64
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• 2022

Breast ultrasonic reading is critical as a primary screening test for the early diagnosis of breast cancer. However, breast ultrasound examinations show significant differences in diagnosis based on the difference in image quality according to the ultrasonic equipment, experience, and proficiency of the examiner. Accordingly, studies are being actively conducted to analyze the texture characteristics of normal breast tissue, positive tumors, and malignant tumors using breast ultrasonography and to use them for computer-assisted diagnosis. In this study, breast ultrasonography was conducted to select 247 ultrasound images of 71 normal breast tissues, 87 fibroadenomas among benign tumors, and 89 malignant tumors. The selected images were calculated using a statistical method with 21 feature parameters extracted using the gray level co-occurrence matrix algorithm, and classified as normal breast tissue, benign tumor, and malignancy. In addition, we proposed five feature parameters that are available for computer-aided diagnosis of breast cancer classification. The average classification rate for normal breast tissue, benign tumors, and malignant tumors, using this feature parameter, was 82.8%.

• Animal Bioscience
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• v.34 no.8
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• pp.1253-1270
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• 2021

Assessment of male fertility is based on the evaluation of sperm. Semen evaluation measures various sperm quality parameters as fertility indicators. However, semen evaluation has limitations, and it requires the advancement and application of strict quality control methods to interpret the results. This article reviews the recent advances in evaluating various sperm-specific quality characteristics and methodologies, with the help of different assays to assess sperm-fertility status. Sperm evaluation methods that include conventional microscopic methods, computer-assisted sperm analyzers (CASA), and flow cytometric analysis, provide precise information related to sperm morphology and function. Moreover, profiling fertility-related biomarkers in sperm or seminal plasma can be helpful in predicting fertility. Identification of different sperm proteins and diagnosis of DNA damage has positively contributed to the existing pool of knowledge about sperm physiology and molecular anomalies associated with different infertility issues in males. Advances in methods and sperm-specific evaluation has subsequently resulted in a better understanding of sperm biology that has improved the diagnosis and clinical management of male factor infertility. Accurate sperm evaluation is of paramount importance in the application of artificial insemination and assisted reproductive technology. However, no single test can precisely determine fertility; the selection of an appropriate test or a set of tests and parameters is required to accurately determine the fertility of specific animal species. Therefore, a need to further calibrate the CASA and advance the gene expression tests is recommended for faster and field-level applications.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.37-44
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• 2010

Recently, the scientific approach to brain engineering is actively being made for effective foreign language learning and diagnosis. In order to supplement the problem of preexistence paper exam, the study aimed to develop a tool for foreign language fluency diagnosis which based on brain engineering. The proposed tools in the paper indirectly measure the aspects of brain information processing by testing learners' 3 abilities of linguistic memory, comprehension, and language production in 5 different ways.

• Journal of radiological science and technology
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• v.28 no.2
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• pp.123-128
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• 2005

It is necessary to obtain images of high diagnosis worth based on ability and skill of radiological technologist in case of acquisition of medical radiologaphy information. In addition, we need the various kinds of education considering individual radiological technologist variation and the organization of clinical education according to the large amount of learning and more expensive knowledge of radiology. In this paper, we implement CAI system for cervical vertebrae fracture radiograph with multimedia authoring tools on web environments. The CAI system can train a new radiological technologist and study a lot of radiological technologist on the cervical vertebrae fracture radiography acquisition based on more objective and systematical data in radiography room. The proposed CAI system is also expected as a useful program which can help to cure patients based on accurate diagnosis as well as obtain radiography more quickly using a technology of radiography acquisition for cervical vertebrae fracture.

• Imaging Science in Dentistry
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• v.42 no.4
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• pp.225-229
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• 2012

Purpose: This study aimed to evaluate the trabecular bone changes after alveolar bone grafting in unilateral cleft lip and palate (UCLP) patients using a computer-aided diagnosis (CAD) system. Materials and Methods: The occlusal radiographs taken from 50 UCLP patients were surveyed retrospectively. The images were categorized as: 50 images in group 0 (before bone grafting), 33 images in group 1 (one month after bone grafting), 24 images in group 2 (2-4 months after bone grafting), 15 images in group 3 (5-7 months after bone grafting), and 21 images in group 4 (8 or more months after bone grafting). Each image was grouped as either "non-cleft side" or "cleft side". The CAD system was used five times for each side to calculate the pixel area based on the mathematical morphology. Significant differences were found using a Wilcoxon signed ranks test or paired samples t test. Results: The pixel area showed a significant difference between the "non-cleft side" and "cleft side" in group 0 ($404.27{\pm}103.72/117.73{\pm}92.25$; p=0.00), group 1 ($434.29{\pm}86.70/388.31{\pm}109.51$; p=0.01), and group 4 ($430.98{\pm}98.11/366.71{\pm}154.59$; p=0.02). No significant differences were found in group 2 ($423.57{\pm}98.12/383.47{\pm}135.88$; p=0.06) or group 3 ($433.02{\pm}116.07/384.16{\pm}146.55$; p=0.19). Conclusion: Based on the design of this study, alveolar bone grafting was similar to normal bone within 2-7 months postoperatively.