• Journal of the Korea Computer Graphics Society
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• v.28 no.1
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• pp.1-9
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• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• Journal of Gastric Cancer
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• v.23 no.1
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• pp.107-145
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• 2023

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.25-32
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• 2023

Constipation is the most common digestive disorder, and it occurs frequently in the early stages and affects the prognosis on rehabilitation stage in the patients with brain injury. The purpose of this study is to evaluate the bowel habits of brain-injured patients undergoing enteral nutrition immediately after admission to rehabilitation and transmission, and to investigate the effects of abdominal massage and lower extremity exercise. The study design is a quasi-experimental study to investigate the effect of a bowel care intervention (abdominal massage and lower extremity exercise) applicable to patients with brain lesions. As a result of the study, the number of bowel movements was significantly higher in the intervention group (p=.030), and the use of suppositories in the control group was statistically significantly higher than that in the intervention group (p=.004). The time of constipation relief was 1.73 days for the experimental group and 4.61 days for the control group, indicating that there was a difference in the time of constipation relief between the two groups (p<.001). Abdominal massage and lower extremity exercise were effective as nursing interventions to relieve constipation and prevent constipation in patients with brain injury from the early stage of rehabilitation.

• Journal of Gastric Cancer
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• v.23 no.2
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• pp.355-364
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• 2023

Background: There are no clear guidelines to determine whether to perform D1 or D1+ lymph node dissection in early gastric cancer (EGC). This study aimed to develop a nomogram for estimating the risk of extraperigastric lymph node metastasis (LNM). Materials and Methods: Between 2009 and 2019, a total of 4,482 patients with pathologically confirmed T1 disease at 6 affiliated hospitals were included in this study. The basic clinicopathological characteristics of the positive and negative extraperigastric LNM groups were compared. The possible risk factors were evaluated using univariate and multivariate analyses. Based on these results, a risk prediction model was developed. A nomogram predicting extraperigastric LNM was used for internal validation. Results: Multivariate analyses showed that tumor size (cut-off value 3.0 cm, odds ratio [OR]=1.886, P=0.030), tumor depth (OR=1.853 for tumors with sm2 and sm3 invasion, P=0.010), cross-sectional location (OR=0.490 for tumors located on the greater curvature, P=0.0303), differentiation (OR=0.584 for differentiated tumors, P=0.0070), and lymphovascular invasion (OR=11.125, P<0.001) are possible risk factors for extraperigastric LNM. An equation for estimating the risk of extraperigastric LNM was derived from these risk factors. The equation was internally validated by comparing the actual metastatic rate with the predicted rate, which showed good agreement. Conclusions: A nomogram for estimating the risk of extraperigastric LNM in EGC was successfully developed. Although there are some limitations to applying this model because it was developed based on pathological data, it can be optimally adapted for patients who require curative gastrectomy after endoscopic submucosal dissection.

• Imaging Science in Dentistry
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• v.53 no.3
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• pp.193-198
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• 2023

Purpose: Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. Materials and Methods: A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type of AI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Results: Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was 91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. Conclusion: AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.581-586
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• 2023

Recently a drama that features a lawyer with autism spectrum disorder has attracted a lot of attention, raising interest in the difficulties faced by people with autism spectrum disorders. If the Autism spectrum gets detected early and proper education and treatment, the prognosis can be improved, so the development of the treatment is urgently needed. Drugs currently used to treat autism spectrum often have side effects, so Digital Therapeutics that have no side effects and can be supplied in large quantities are drawing attention. In this paper, we introduce 'AEmotion', an application and a Digital Therapeutic that provides emotion and facial expression learning for toddlers with an autism spectrum disorder. This system is developed as an application for smartphones to increase interest in training autistic children and to test easily. Using machine learning, this system consists of three main stages: an 'emotion learning' step to learn emotions with facial expression cards, an 'emotion identification' step to check if the user understood emotions and facial expressions properly, and an 'expression training' step to make appropriate facial expressions. Through this system, it is expected that it will help autistic toddlers who have difficulties with social interactions by having problems recognizing facial expressions and emotions.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.2
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• pp.125-134
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• 2023

When the patient with class III malocclusion needs extensive oral rehabilitation due to multiple missing teeth, accurate diagnosis, and careful analysis, such as the patient's occlusal relationship, facial changes, and evaluation of the temporomandibular joint are essential. Orthognathic surgery is often performed for aesthetic improvement, depending on the patient's chief complaint. If it is not possible due to certain circumstances, partial aesthetic improvement can be achieved through minimal elevation of the vertical dimension. As this patient may have unexpected issues, such as temporomandibular joint disorder, oral habits like bruxism, and masticatory muscle tension, it was determined whether the patient could adjust to a reversible temporary removable partial denture. After this, the maxillary implant-supported fixed prostheses and the mandibular fixed prostheses were used to achieve stable posterior support and to partially improve the maxillary anterior esthetics. The patient was satisfied with the results both aesthetically and functionally. The prognosis is expected to be good if regular check-ups are conducted.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.1
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• pp.1-8
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• 2023

Purpose: The purpose of this study is to analyze the prognostic factors related to tooth loss after 5 years of periodontal surgery in periodontal disease patients. Materials and Methods: From January to December 2017, 22 patients and 124 teeth who underwent periodontal treatment through periodontal surgery were targeted. At the time of treatment, the measured values were evaluated after recording the maximum probing depth, average periodontal probing depth, number of root, furcation involvement, pulp vitality, and prosthesis state on the day of periodontal surgery. Based on the initial records at the time of visit, patient-related factors were gender, age, smoking, tooth loss due to periodontal disease at the time of first visit, diabetes, and maintenance period. The influence of each factor on tooth loss was evaluated. Results: As a result of examining the influence of tooth-related factors on tooth loss, the maximum probing depth depth (P: 0.000), bone loss (P: 0.021) was found to have a significant effect on tooth loss. Conclusion: As a result of examining the influence of patient-related factors on tooth loss, any variables had no significant effect. Bone loss, maximum probing depth acted as statistically significant prognostic factors for tooth loss in patients who underwent periodontal surgery.

• Journal of Trauma and Injury
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• v.36 no.1
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• pp.22-31
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• 2023

Purpose: Traumatic brain injury (TBI) directly affects the survival of patients and can cause long-term sequelae. The purpose of our study was to investigate whether the operation of a trauma center in a single tertiary general hospital has improved emergency care and clinical outcomes for patients with TBI. Methods: The participants of this study were all TBI patients, patients with isolated TBI, and patients with TBI who underwent surgery within 24 hours, who visited our level 1 trauma center from March 1, 2012 to February 28, 2020. Patients were divided into two groups: patients who visited before and after the operation of the trauma center. A comparative analysis was conducted. Differences in detailed emergency care time, hospital stay, and clinical outcomes were investigated in this study. Results: On comparing the entire TBI patient population via dividing them into the aforementioned two groups, the following results were found in the group of patients who visited the hospital after the operation of the trauma center: an increased number of patients with a good functional prognosis (P<0.001 and P=0.002, respectively), an increased number of surviving discharges (P<0.001 and P<0.001, respectively), and a reduction in overall emergency care time (P<0.05, for all item values). However, no significant differences existed in the length of intensive care unit stay, ventilator days, and total length of stay for TBI patients who visited the hospital before and after the operation of the trauma center. Conclusions: The findings confirmed that overall TBI patients and patients with isolated brain injury had improved treatment results and emergency care through the operation of a trauma center in a tertiary general hospital.

• The korean journal of orthodontics
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• v.53 no.2
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• pp.77-88
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• 2023

Objective: To develop a method for generating three-dimensional (3D) digital models of the periodontal ligament (PDL) using 3D cone-beam computed tomography (CBCT) reconstruction and to evaluate the accuracy and agreement of the 3D PDL models in the measurement of periodontal bone loss. Methods: CBCT data collected from four patients with skeletal Class III malocclusion prior to periodontal surgery were reconstructed at three voxel sizes (0.2 mm, 0.25 mm, and 0.3 mm), and 3D tooth and alveolar bone models were generated to obtain digital PDL models for the maxillary and mandibular anterior teeth. Linear measurements of the alveolar bone crest obtained during periodontal surgery were compared with the digital measurements for assessment of the accuracy of the digital models. The agreement and reliability of the digital PDL models were analyzed using intra- and interexaminer correlation coefficients and Bland-Altman plots. Results: Digital models of the maxillary and mandibular anterior teeth, PDL, and alveolar bone of the four patients were successfully established. Relative to the intraoperative measurements, linear measurements obtained from the 3D digital models were accurate, and there were no significant differences among different voxel sizes at different sites. High diagnostic coincidence rates were found for the maxillary anterior teeth. The digital models showed high intra- and interexaminer agreement. Conclusions: Digital PDL models generated by 3D CBCT reconstruction can provide accurate and useful information regarding the alveolar crest morphology and facilitate reproducible measurements. This could assist clinicians in the evaluation of periodontal prognosis and establishment of an appropriate orthodontic treatment plan.