• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.678-700
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• 2023

Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.860-880
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• 2024

Breast cancer is a major health concern affecting women and men globally. Early detection and accurate classification of breast cancer are vital for effective treatment and survival of patients. This study addresses the challenge of accurately classifying breast tumors using machine learning classifiers such as MLP, AdaBoostM1, logit Boost, Bayes Net, and the J48 decision tree. The research uses a dataset available publicly on GitHub to assess the classifiers' performance and differentiate between the occurrence and non-occurrence of breast cancer. The study compares the 10-fold and 5-fold cross-validation effectiveness, showing that 10-fold cross-validation provides superior results. Also, it examines the impact of varying split percentages, with a 66% split yielding the best performance. This shows the importance of selecting appropriate validation techniques for machine learning-based breast tumor classification. The results also indicate that the J48 decision tree method is the most accurate classifier, providing valuable insights for developing predictive models for cancer diagnosis and advancing computational medical research.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.45-57
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• 2024

Objectives: The purpose of this study is to determine the impact of artificial menopause on the diagnosis of thyroid cancer, breast cancer, and cervical cancer, and to provide basic data for cancer prevention and early diagnosis in women. Methods: Analysis was conducted using raw data from the 2011-2020 National Health and Nutrition Examination Survey. Among the 79,262 people surveyed in the 2011-2020 National Health and Nutrition Examination Survey, 10,207 people were selected as the final research subjects, excluding men, those under 18 years old, those over 80 years old, those who did not participate in the health survey, those with missing data, and those who were not in menopause. Among them, 248 people were diagnosed with thyroid cancer (2.7%), 225 people were diagnosed with breast cancer (2.5%), and 143 people were diagnosed with cervical cancer (21.5%). Results: First, there appeared to be differences between the thyroid cancer diagnosed group and the non-diagnosed group depending on educational level, childbirth experience, and menopause type. Second, there appeared to be differences between the breast cancer diagnosis group and the non-diagnosis group depending on educational level, menopause age, pregnancy experience, childbirth experience, subjective health status, and menopause type. Third, there appeared to be differences between the cervical cancer diagnosis group and the non-diagnosis group depending on menopause age, subjective health status, and menopause type. Fourth, compared to natural menopause, in the case of artificial menopause, the diagnosis probability of women increased by 2.010 times for thyroid cancer, 3.872 times for breast cancer, and 14.902 times for cervical cancer. Conclusion: For thyroid cancer, breast cancer, and cervical cancer, the probability of cancer diagnosis increases in the case of artificial menopause compared to natural menopause, so it is considered important to avoid experiencing artificial menopause to prevent cancer.

• Child Health Nursing Research
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• v.1 no.1
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• pp.37-46
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• 1995

The effects of different discharge packs on the rate of breast-feeding practice were investigated in 2, 4 and 8 postpartal weeks. The subjects were those who have made delivery at Chonnam University Hospital from Jan to Feb 1994. They were divided into three groups by the discharge pack provided at the nursery room : the one group was given with formula discharge pack, another with breast-feeding discharge pack and the other nothing. The formula discharge pack contained formula samples, a feeding bottle and a pamphlet prepared by a formula company, and breast-feeding discharge pack contained a manual pump and a pamphlet made by Korean Nurses Association. Following results were obtained : 1. Different discharge packs significantly affected the rate of breast-feeding practice at 2 week postpartum, while not at 4 and 8 week postpartum. 2. At 2 week postpartum, the rate of breast-feeding practice was significantly higher in the group given with breast-feeding discharge pak than in that given with formula discharge pack. It was also significantly higher in the group given with breast-feeding discharge pack compared with the group given nothing. The breast feeding rate, however, did not significantly differ between the formula discharge pack group and the group given nothing. 3. The most common cause for the artificial feeding was 'lacking breast milk'. The most common cause to select a specific brand of formula milk was 'the same as in the nursery room'. In conclusion, it is suggested that encouraging mothers to perform breast feeding and providing them with a breast-feeding discharge pack instead of a formula pack at the nursery room are helpful in promoting the breast-feeding.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.421-424
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• 2005

X-ray is currently most effective method in detecting small malignant breast tumors but has the several problems due to suppressing breast, ionizing radiation and not detecting small cancer. In this paper, a new method is proposed by using dielectric characteristics of pathological tissues and time delay of backscattered response. We have developed a detection algorithm and verified it by numerical simulation and measurement for a prototype system. For a prototype system, we have fabricated experimental model(artificial breast with a cancer) and UWB(ultra-wideband) antenna. The results of the measurement simulation show an excellent detection capability of a cancer tissue. It is found that a good UWB antenna is a key element of such detection system. Further study is ongoing to develop a commercial system.

• Korean Journal of Radiology
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• v.23 no.2
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• pp.153-155
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• 2022

• Korean Journal of Radiology
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• v.25 no.4
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• pp.343-350
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• 2024

Objective: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings. Materials and Methods: From March 2020 to May 2022, 656 breasts from 599 women (mean age 52.6 ± 11.5 years, including 0.6% [4/599] high-risk women) who underwent mammography and received positive AI-CAD results (Lunit Insight MMG, abnormality score ≥ 10) were retrospectively included in this study. Univariable and multivariable analyses were performed to evaluate the associations between the AI-CAD abnormality scores and clinical and radiological factors. The breasts were subdivided according to the abnormality scores into groups 1 (10-49), 2 (50-69), 3 (70-89), and 4 (90-100) using the optimal binning method. The PPVs were calculated for all breasts and subgroups. Results: Diagnostic indications and positive imaging findings by radiologists were associated with higher abnormality scores in the multivariable regression analysis. The overall PPV of AI-CAD was 32.5% (213/656) for all breasts, including 213 breast cancers, 129 breasts with benign biopsy results, and 314 breasts with benign outcomes in the follow-up or diagnostic studies. In the screening mammography subgroup, the PPVs were 18.6% (58/312) overall and 5.1% (12/235), 29.0% (9/31), 57.9% (11/19), and 96.3% (26/27) for score groups 1, 2, 3, and 4, respectively. The PPVs were significantly higher in women with diagnostic indications (45.1% [155/344]), palpability (51.9% [149/287]), fatty breasts (61.2% [60/98]), and certain imaging findings (masses with or without calcifications and distortion). Conclusion: PPV increased with increasing AI-CAD abnormality scores. The PPVs of AI-CAD satisfied the acceptable PPV range according to Breast Imaging-Reporting and Data System for screening mammography and were higher for diagnostic mammography.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.361-367
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• 2016

We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in $R^2$ from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects.

• 모자간호학회지
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• v.3 no.2
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• pp.166-171
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• 1993

To compare the morbidity between the breast-fed and artificial formula-fed Infants, the frequency of diseases during infancy was studied. The subjects were 37 breast-fed infants and 41 formula-fed infants aged 12-15 months. The data were obtained while they visited the pediatric out-patient clinics. The results were as follows : 1. Most prevalent diseases in the infancy were respiratory and gastrointestinal illnesses. 2. During the first 6 months the morbidity was significantly lower in the breast-fed than in the formula-fed 3. The frequency of respiratory and gastrointestinal diseases was significantly higher in the formula-fed than in the breast-fed infant during the first 6 months.

• 모자간호학회지
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• v.4 no.1
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• pp.52-67
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• 1994

This study was done to investigate mother's attitude to breast feeding and the type of feeding according to the general characteristics of mother. The study sample consisted of 1696 mothers who had an infant and who were visiting five Hospitals or ten Public Health Centers in Seoul. Data was collected through a question aire from June, 1 to June, 30, 1993. The results are as follows : 1. The types of feeding were artificial feeding 2%), mixed feeding(21.7%) and breast feeding (26.1%). 2. The attitude of mothers to breast feeding was very positive for behavior tendency and cognitive attitude but the emotional attitude was low to moderate. 3. The attitude scores for the mothers were from 27 to 60 and 65% the mothers had scores that were high, 50-60 and mean was 49.86. 4. There was the significance between the general characteristics (type of delivery, obtaining in formation on breast feeding, type of feeding and baby's birth order) and the attitude score of mothers. 5. The attitude scores for the mothers by the general characteristics and type of feeding was not a 2-way interaction but the type of feeding had a main effects.