• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.4813-4820
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• 2015

Gastric cancer (GC) is one of the most common cancers, with high incidences in East Asia countries. Most GC patients have been reported with low early diagnosis rate and show extremely poor prognosis. Therefore, it is necessary to develop novel and more sensitive biomarkers to improve early diagnosis and therapy in order to provide longer survival and better quality of life for gastric cancer patients. MicroRNAs (miRNAs) play crucial roles in GC development and progression. miRNAs have emerged as a novel molecular biomarker for cancer diagnosis, prognosis and therapy with surprising stability in tissues, serum or other body fluids. This review summarizes major advances in our current knowledge about potential miRNA biomarkers for GC that have been reported in the past two years.

• 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%.

• Clinical Endoscopy
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• v.57 no.1
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• pp.11-17
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• 2024

Although magnifying endoscopy with narrow-band imaging is the standard diagnostic test for gastric cancer, diagnosing gastric cancer using this technology requires considerable skill. Artificial intelligence has superior image recognition, and its usefulness in endoscopic image diagnosis has been reported in many cases. The diagnostic performance (accuracy, sensitivity, and specificity) of artificial intelligence using magnifying endoscopy with narrow band still images and videos for gastric cancer was higher than that of expert endoscopists, suggesting the usefulness of artificial intelligence in diagnosing gastric cancer. Histological diagnosis of gastric cancer using artificial intelligence is also promising. However, previous studies on the use of artificial intelligence to diagnose gastric cancer were small-scale; thus, large-scale studies are necessary to examine whether a high diagnostic performance can be achieved. In addition, the diagnosis of gastric cancer using artificial intelligence has not yet become widespread in clinical practice, and further research is necessary. Therefore, in the future, artificial intelligence must be further developed as an instrument, and its diagnostic performance is expected to improve with the accumulation of numerous cases nationwide.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5869-5873
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• 2015

Background: Breast and cervical cancers are among the most frequent and most fatal cancers in women. Life span of patients may be increased and quality of life improved through early diagnosis and treatment. This investigation was performed in order to determine knowledge and practices of female health personnel working at a university hospital regarding breast and cervical cancers. Materials and Methods: This descriptive investigation was performed in Erciyes University Hospitals in 2014. A total of 524 female health personnel were included in the study. Data were collected through a questionnaire of 36 questions prepared by the researchers. The Chi square test and logistic regression were used for statistical analyses. Results: The mean age of the study group was $32.8{\pm}6.9$ years, 18.3% being doctors and 81.7% nurses. Of the study group, 60.5% stated that they performed self breast-examination, 4.4% underwent HPV testing, 26.3% thought about taking an HPV test, 34.7% of those who are 40 years and over had mammography regularly and 19.5% of those who were married had a Pap smear conducted regularly. Most important causes of not performing the methods for early diagnosis of breast and cervical cancers are "forget and neglect". Conclusions: It was concluded that female doctors and nurses do not pay sufficient attention to screening programs for breast and cervical cancers. The importance of early diagnosis and treatment should be emphasized during the undergraduate education and in-service training programs. Health condition of personnel and their utilization of preventive health care should be followed by occupational physicians.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.11
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• pp.4647-4652
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• 2015

Background: Colorectal cancer (CRC) is becoming one of the most complicated challenges of human health, particularly in developing countries like Iran. In this paper, we try to characterize CRC cases diagnosed < age 50 at-risk for Lynch syndrome within central Iran. Materials and Methods: We designed a descriptive retrospective study to screen all registered CRC patients within 2000-2013 in Poursina Hakim Research Center (PHRC), a referral gastroenterology clinic in central Iran, based on being early-onset (age at diagnosis ${\leq}50years$) and Amsterdam II criteria. We calculated frequencies and percentages by SPSS 19 software to describe clinical and family history characteristics of patients with early-onset CRC. Results: Overall 1,659 CRC patients were included in our study of which 413 (24.9%) were ${\leq}50years$ at diagnosis. Of 219/413 successful calls 67 persons (30.6%) were reported deceased. Family history was positive for 72/219 probands (32.9%) and 53 families (24.2%) were identified as familial colorectal cancer (FCC), with a history of at-least three affected members with any type of cancer in the family, of which 85% fulfilled the Amsterdam II Criteria as hereditary non-polyposis colorectal cancer (HNPCC) families (45/219 or 20.5%). Finally, 14 families were excluded due to proband tumor tissues being unavailable or unwillingness for incorporation. The most common HNPCC-associated extracolonic-cancer among both males and females of the families was stomach, at respectively 31.8 and 32.7 percent. The most common tumor locations among the 31 probands were rectum (32.3%), sigmoid (29.0%), and ascending colon (12.9%). Conclusions: Given the high prevalence of FCC (~1/4 of early-onset Iranian CRC patients), it is necessary to establish a comprehensive cancer genetic counseling and systematic screening program for early detection and to improve cancer prognosis among high risk families.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.68-80
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• 2013

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.10
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• pp.4723-4727
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• 2016

Background: There are substantial differences in the mortality rates of stomach cancer among the 47 prefectures in Japan, and Aomori prefecture is one of the most severely impacted. The aims of this study were to determine the incidence and mortality rates of stomach cancer in Aomori prefecture in comparison with Japan as a whole and cast light on reasons underlying variation. Methods: Data on stomach cancer cases were extracted from the Aomori Cancer Registry Database. Incidence rates for specific stages at the time of diagnosis were cited from Monitoring of Cancer Incidence in Japan, and mortality rates for stomach cancer in Aomori prefecture and the whole of Japan were obtained from Vital Statistics. Age-standardised incidence and mortality rates were calculated using the direct method. Results: The age-standardised incidence rate of stomach cancer in Aomori prefecture was higher than in the whole of Japan for males but lower for females. However, the age-standardised mortality rates were higher in Aomori prefecture in both sexes. The proportion of localised cancers was lower in Aomori prefecture than in the whole of Japan for most age groups. Conclusions: The lower rate for localised cancer suggests that higher age-standardised mortality rates are due to delays in diagnosis, despite an attendance rate for stomach cancer screening was higher in Aomori prefecture than in the whole of Japan. One plausible explanation for the failure of successful early detection might be poor quality control during screening implementation that impedes early detection.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2501-2505
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• 2015

Purpose: The present study was carried out to measure knowledge level and behavior of family health personnel (FHP) in Izmir on early diagnosis of breast and cervical cancers. Materials and Methods: The study population of this cross-sectional study was not selected. A questionnaire was applied to all FHP to measure knowledge level and behavior about cancer. The participation rate was 88%. Breast examination, mammography analysis, Papanicolaou smear applications were determined as dependent variables, and knowledge level about breast and cervical cancer, age, professional time as FHP as independent variables. Data were evaluated using definitive statistics, chi-square and logistic regression tests in SPSS software package for Windows 15.0. Results: A total of 970 family health personnel participated in the research. The age range was 20-45 years (82.4%). Mean age was $37.9{\pm}7.4$. Response rate was 87.3%. Of the participants, 88.4% performed breast self-examination. Rate of performing mammography at least once was 24.1%. Rate of performing Pap-smear examination at least once was 61.0%. In logistic regression analyses, it was determined that people with knowledge on breast and cervical cancer were those performing breast self-examination, mammography and Pap-smear examinations (p<0.05. Conclusions: It is essential that the knowledge, behavior and manners of health providers on early diagnosis for cancer increases awareness in the general population and provides information on execution ofthe most effective methods for generating a healthy society.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1767-1770
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• 2012

Background: The Asia Pacific consensus for colorectal cancer (CRC) recommends that screening programs should begin by the age of 50. However, there have been reports about increasing incidence of CRC at a younger age (i.e. early-onset CRC). Little is known about the features of early-onset CRC in the Vietnamese population. Aim: To describe the clinical, endoscopic and pathological characteristics of early-onset CRC in Vietnamese. Method: A prospective, cross-sectional study was conducted at the University Medical Center from March 2009 to March 2011. All patients with definite pathological diagnosis of CRC were recruited. The early-onset CRC group were analyzed in comparison with the late-onset (i.e. ${\geq}$ 50-year-old) CRC group. Results: The rate of early-onset CRC was 28% (112/400) with a male-to-female ratio of 1.3. Some 22.3% (25/112) of the patients only experienced abdominal pain and/or change in bowel habit without alarming symptoms, 42.9% (48/112) considering their symptoms intermittent. The rate of familial history of CRC in early-onset group was significantly higher that of the late-onset group (21.4% versus 7.6%, p<0.001). The distribution of CRC lesions in rectum, distal and proximal colon were 51.8% (58/112), 26.8% (30/112) and 21.4% (24/112), respectively; which was not different from that in the late-onset group (${\chi}2$, p = 0.29). The rates for poorly differentiated tumors were also not significantly different between the two groups: 12.4% (14/112) versus 8.3% (24/288) (${\chi}2$, p = 0.25). Conclusion: A high proportion of CRC in Viet Nam appear at an earlier age than that recommended for screening by the Asia Pacific consensus. Family history was a risk factor of early-onset CRC. Diagnosis of early-onset CRC needs more attention because of the lack of alarming symptoms and their intermittent patterns as described by the patients.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.375-387
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• 2023

Stomach cancer has a high annual mortality rate worldwide necessitating early detection and accurate treatment. Even experienced specialists can make erroneous judgments based on several factors. Artificial intelligence (AI) technologies are being developed rapidly to assist in this field. Here, we aimed to determine how AI technology is used in gastric cancer diagnosis and analyze how it helps patients and surgeons. Early detection and correct treatment of early gastric cancer (EGC) can greatly increase survival rates. To determine this, it is important to accurately determine the diagnosis and depth of the lesion and the presence or absence of metastasis to the lymph nodes, and suggest an appropriate treatment method. The deep learning algorithm, which has learned gastric lesion endoscopyimages, morphological characteristics, and patient clinical information, detects gastric lesions with high accuracy, sensitivity, and specificity, and predicts morphological characteristics. Through this, AI assists the judgment of specialists to help select the correct treatment method among endoscopic procedures and radical resections and helps to predict the resection margins of lesions. Additionally, AI technology has increased the diagnostic rate of both relatively inexperienced and skilled endoscopic diagnosticians. However, there were limitations in the data used for learning, such as the amount of quantitatively insufficient data, retrospective study design, single-center design, and cases of non-various lesions. Nevertheless, this assisted endoscopic diagnosis technology that incorporates deep learning technology is sufficiently practical and future-oriented and can play an important role in suggesting accurate treatment plans to surgeons for resection of lesions in the treatment of EGC.