• Fashion & Textile Research Journal
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• v.22 no.1
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• pp.76-86
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• 2020

The study surveyed patients undergoing a mastectomy to understand their experience and requirements on artificial breasts and sales status. We retrieved 149 of the 150 surveyed questionnaires; subsequently, 144 questionnaires, excluding missing values, were used in the analysis. According to the results of the study, about 67% of respondents said that artificial breasts were not used after undergoing a mastectomy, and more than half of the breast cancer patients were not aware of the importance of artificial breasts. Breast cancer patients wearing artificial breast felt uncomfortable and hot during daily activities as well as experienced difficulty in size selection and purchase price burdens. The three most responded brands were selected based on the results of the survey that also investigated the sales status of the commercial artificial breast. Company A was selling artificial breast to reflect the consumer's functional requirements, and Company C was selling artificial breast with various kinds of reduced weight. However, it is thought that consumers will have less choice since artificial breasts have more limited forms than various types. Therefore, it is believed that the patient needs artificial breasts that satisfy the shape of various types of mastectomy. This study can be used as basic data for artificial breast development studies.

• Journal of Korean Academy of Nursing
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• v.23 no.3
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• pp.377-398
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• 1993

A survey of infant practices was conducted to provide information on which to base planned nursing interventions. The subjects were a convenience sample of 168 mothers visiting out - patients departments of five general hospitals and one public health center in Seoul for immunizations or treatment for common colds for their infants from two to 12 months of age. Data collection was carried out from July 8th to September 30th, 1991 using a questionnaire of 84 questions, 31 on the type of feeding, 22 on supplementary feeding and 21 on demographic infer mation. The results are summarized as follows : 1) The type of feeding was primarily artificial feed-ing (63.1%), followed by mixed feeding (22%) and breast feeding (14.9%) of the 59 mothers expecting during pregnancy to breast feed, 54. 2% changed artificial feeding and 30.5% went on to breast feed as they had expected. For mothers expecting to continue breast feeding over seven months. only one infant was being breast fed for over seven months. 2) For the 106 mothers using artificial feeding, 70. 8% hed attempted breast feeding, 64% of them for less than a month. Breast milk had been suppressed by for medication (38.7%) : 34.9% had used no specia] means. 3) The major reasons for replacing breast feeding with artificial feeding were the infants' demand for more milk (47.2% ) and insufficient supply of breast milk (49.3％). 4) Most mixed feeding was started at the age of one to three months (59.5%). Only 34.4% gave an artificial feeding after breast feeding : most (46%) alternated breast feeding with artificial feeding. On the whole, the motive for mixed feeding was the lack of breast milk (70.3%). 5) Many mothers (81.8%) were adding vitamin or mineral supplements to artificial milk and 51.5% were adding something to faciliate digestion. As for the method of sterilizing milk bottles and nipples, 56% had sterilized them together in boiling water from the beginning : 27% were just washing the bottles after boiling only once initially when measuring artificial milk powder, 31. 5% of the mothers over filled the measuring spoon rather than to the level. 6) The mother's occupation was related to her way of feeding. Mothers at home full time did more breast feeding than mothers employed outside the home. (x²=5.72, p=〈0.05). 7) Most mothers began supplementary food, from three to four months (48.8%) : 11.2% began later than seven months. Supplementary food was given between milk feedings by 67.2% of the mothers : 19.2% gave it before a milk feeding. Some mothers(26.4%) made their own supplementary food : 19.2% used ready - made supplementary food products for convenience. Recommendations for nursing interventions included : 1. Prenatal education about the advantages of breast feeding and breast care, and home visits after delivery for counselling related to breast feeding. Correct preparation of artificial feeding methods need to be taught in both pre & postnatal periods. In addition, specific education about supplementary feeding needed. 2. Further research is indicated about the Perceived lack of supply of breast milk and about the effectiveness of nursing interventions to Promote breast feeding.

• Journal of Preventive Medicine and Public Health
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• v.15 no.1
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• pp.167-177
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• 1982

This study was undertaken to observe relationships between patterns of feeding, supplementary-feeding and various maternal, family, and socioeconomic charactereistics in Hae Cheog Apartment area in Cheongdam-dong, Kangnamku, Seoul on July 2 to 12 in 1982. The results were based on a questionnaire from 179 mothers who have the last-born child under two years old. Results were as follows: 1) In socio-demographic characteristics, most of mothers were 25 to 30 years old and 52.0% of index children were under 6 months old. About 56.0% of families were the salaries and 47.0% of them earn over 500,000 won a month. 40.8% of mothers were college graduates and 81.6% of mothers had no occupation. 2) 89.4% of mothers received prenatal care in pregnancy of the index children and mothers who have delivered the child in medical institute were 88.3%. Mothers who recieved education of breast care and feeding technique through prenatal care were 22.4%, 31.8% respectively. 3) In the feeding method, 44.1% of mothers took the breast feeding, 24.0% of them chose the artificial feeding, and 20.7% of them chose the mixed feeding. Mothers who changed the-method from breast feeding to artificial feeding were 10.6% and only 0.6% of mothers changed from artificial feeding to breast feeding. 4) According to the questionnaire, 37 mothers have already finished lactation (no relation with. the beginning of weaning food). In breast feeding, one mother has lactated for $4{\sim}6$ months, one has lactated for $7{\sim}9$ months, four have lactated for $10{\sim}12$ months, and seven have. continued the lactation over 12 months. In artificial and mixed feeding, as the same phenomenon, most of mothers have lactated for more than 12 months. 5) The reasons for feeding method were as follows: In breast feeding, 64.6% of them took the method because they thought the breast milk nutrious, in artificial feeding, 34.9% of them chose it because they had occupation and in the mixed feeding, 67.6% of mothers took the method because of lack of their breast milk. In the case of changing the method from breast feeding to artificial feeding, 42.1% of them answered that they had to change the method because of lack of breast milk. 6) In most of cases, the 4th month was the proper period to begin the weaning food and 32.5% of breast feeding children and 27.6% of artificial feeding children began the weaning food in 4th month. After 4th month, there was no difference between breast feeding and artificial feeding in the beginning of weaning food. 7) In the matter of menstruation, 29.8% of mothers who had breast feeding started their menstruations in 3 months and the rest of them delayed until 12 months. 40% of mothers who had artificial feeding began to menstruate after 2 months and all the rest started within 5 months. 8) The birth interval between the index child and next new child (would-be-born): In breast feeding, the interval of $18{\sim}24$ months had a majority as 50.0%, and in the artificial feeding, the interval of over 24 months marked 66.7% of them. It was analyzed that the birth interval of artificial feeding was wider than that of breast feeding. 9) In the desirable number of children, the mothers who had breast feeding wanted two sons and two daughters as proper children. Those who want two children in disregard of the sex (son or daughter) were 89.3% of breast feeding, and 80.0% of artificial feeding respectively. Mothers who had breast feeding wanted two children rather than one child. 10) In the family planning practice, the rate of practice were 41.9% in breast feeding, and 58.1% in artificial feeding respectively. In the case of breast feeding, the using rate of family planning practice in men was higher than in women.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.11-15
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• 2018

Breast cancer is one of the leading causes of cancer related death among women. So prediction of overall survival status is important into decided in adjuvant treatment. Deep belief network is a kind of artificial intelligence (AI). We intended to construct prediction model by deep belief network using associated clinicopathologic factors. 103881 cases were found in the Korean Breast Cancer Registry. After preprocessing of data, a total of 15733 cases were enrolled in this study. The median follow-up period was 82.4 months. In univariate analysis for overall survival (OS), the patients with advanced AJCC stage showed relatively high HR (HR=1.216 95% CI: 0.011-289.331, p=0.001). Based on results of univariate and multivariate analysis, input variables for learning model included 17 variables associated with overall survival rate. output was presented in one of two states: event or cencored. Individual sensitivity of training set and test set for predicting overall survival status were 89.6% and 91.2% respectively. And specificity of that were 49.4% and 48.9% respectively. So the accuracy of our study for predicting overall survival status was 82.78%. Prediction model based on Deep belief network appears to be effective in predicting overall survival status and, in particular, is expected to be applicable to decide on adjuvant treatment after surgical treatment.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.12-28
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• 2021

Mammography is the primary imaging modality for breast cancer detection; however, a high level of expertise is needed for its interpretation. To overcome this difficulty, artificial intelligence (AI) algorithms for breast cancer detection have recently been investigated. In this review, we describe the characteristics of AI algorithms compared to conventional computer-aided diagnosis software and share our thoughts on the best methods to develop and validate the algorithms. Additionally, several AI algorithms have introduced for triaging screening mammograms, breast density assessment, and prediction of breast cancer risk have been introduced. Finally, we emphasize the need for interest and guidance from radiologists regarding AI research in mammography, considering the possibility that AI will be introduced shortly into clinical practice.

• Child Health Nursing Research
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• v.2 no.2
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• pp.35-44
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• 1996

The purpose of this study was to examine the knowledge and attitude of breast feeding and to explore the predictive variables for the intention of breast feeding of mothers. One hundred and thirty-five mothers who delivered at the D University hospital during the period of May to June in 1996 comprised the sample. Data were collected by questionnaire methods before discharge at the hospital. Data were analyzed using percent, 1-test, and logistic regression. The results were as follows : 1. During their pregnancy, majority of mothers (74.8%) got the breast feeding information. Information sources were book (34.5%), family and relatives(32.4%), mass media(24.3%), and professionals such as nurses and doctors (8.8% ). The frequently reported sources of most encouragement for breast feeding were mother in law(20.7%) and baby's father (11.1% ). 2. The mean score of the items of Knowledge and Attitude toward Breast Feeding Scale were 42.56 (SD=5.47) and 39.07(SD=5.15) , representing positive attitude toward breast feeding. The correlation between knowledge and attitude score was significant(r 〓.54, p<.001). Knowledge of breast feeding were significantly different between breast feeding intention group (including partial breast feeding) and artificial feeding intention group(t=2.79, p<.01) 3. Logistic regression analysis revealed that feeding method in the hospital, delivery type, knowledge toward breast feeding, disease related to pregnancy, complication related to delivery, and educational level of mother were predictives of the intention of breast feeding. 4. The most frequently rated reasons for the plan for mixed feeding were concern about insufficient milk (37.9%) and work(27.6%), The major reasons for plan for artificial milk feeding were having premature baby(25.9%) and maternal health problems including infection(14.8% ) and drug use due to chronic illness (14.8%). From the result of the study, it is recommended to develop supportive nursing intervention strategy to promote breast-feeding intention and practice. The intervention could be more effective to begin early in pregnancy and include teaching for breast feeding skills as well as information provision for positive attitude formation.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1225-1239
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• 2021

During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results in the quantitative assessment of parenchymal density, detection and diagnosis of breast cancer, and prediction of breast cancer risk, enabling more precise patient management. AI-based algorithms may also enhance the efficiency of the interpretation workflow by reducing both the workload and interpretation time. However, more in-depth investigation is required to conclusively prove the effectiveness of AI-based algorithms. This review article discusses how AI algorithms can be applied to mammography interpretation as well as the current challenges in its implementation in real-world practice.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5883-5888
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• 2014

Background: Breast cancer is the most common cancers in female populations. The exact cause is not known, but is most likely to be a combination of genetic and environmental factors. Log-logistic model (LLM) is applied as a statistical method for predicting survival and it influencing factors. In recent decades, artificial neural network (ANN) models have been increasingly applied to predict survival data. The present research was conducted to compare log-logistic regression and artificial neural network models in prediction of breast cancer (BC) survival. Materials and Methods: A historical cohort study was established with 104 patients suffering from BC from 1997 to 2005. To compare the ANN and LLM in our setting, we used the estimated areas under the receiver-operating characteristic (ROC) curve (AUC) and integrated AUC (iAUC). The data were analyzed using R statistical software. Results: The AUC for the first, second and third years after diagnosis are 0.918, 0.780 and 0.800 in ANN, and 0.834, 0.733 and 0.616 in LLM, respectively. The mean AUC for ANN was statistically higher than that of the LLM (0.845 vs. 0.744). Hence, this study showed a significant difference between the performance in terms of prediction by ANN and LLM. Conclusions: This study demonstrated that the ability of prediction with ANN was higher than with the LLM model. Thus, the use of ANN method for prediction of survival in field of breast cancer is suggested.

• Korean Journal of Radiology
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• v.24 no.5
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• pp.378-383
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• 2023

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.10
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• pp.4661-4664
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• 2016

Background: Artificial light at night (ALAN) has been linked to increased risk of cancers in body sites like the breast and colorectum. However exposure of ALAN as an environmental risk factor and its relation to cancers in humans has never been studied in detail. Objective: To explore the association of ALAN with all forms of cancers in 158 countries. Materials and Methods: An ecological study encompassing global data was conducted from January to June 2015, with age-standardized rates (ASR) of cancers as the outcome measure. ALAN, in the protected areas, as the exposure variable, was measured with reference to the Protected Area Light Pollution Indicator (PALI) and the Protected Area Human Influence Indicator (PAHI). Pearson's correlations were calculated for PALI and PAHI with ASR of cancers for 158 countries, adjusted for country populations, electricity consumption, air pollution, and total area covered by forest. Stratified analysis was conducted according to the country income levels. Linear regression was applied to measure the variation in cancers explained by PALI and PAHI. Results: PALI and PAHI were positively associated with ASR of all forms of cancer, and also the four most common cancers (p < 0.05). These positive correlations remained statistically significant for PAHI with all forms of cancer, lung, breast, and colorectal cancer after adjusting for confounders. Positive associations of PALI and PAHI with cancers varied with income level of the individual countries. Variation in all forms of cancers, and the four most common cancers explained by PALI and PAHI, ranged from 3.3 - 35.5%. Conclusion: Artificial light at night is significantly correlated for all forms of cancer as well as lung, breast, colorectal, and prostate cancers individually. Immediate measures should be taken to limit artificial light at night in the main cities around the world and also inside houses.