Osong Public Health and Research Perspectives

Original Articles

BCED-Net: Breast Cancer Ensemble Diagnosis Network using transfer learning and the XGBoost classifier with mammography images: Drishti Arora, Rakesh Garg, Farhan Asif; Osong Public Health Res Perspect. 2024;15(5):409-419. Published online September 10, 2024; DOI: https://doi.org/10.24171/j.phrp.2023.0361

922 View
39 Download

Graphical Abstract Abstract PDF: Objectives
Breast cancer poses a significant global health challenge, characterized by complex origins and the potential for life-threatening metastasis. The critical need for early and accurate detection is underscored by the 685,000 lives claimed by the disease worldwide in 2020. Deep learning has made strides in advancing the prompt diagnosis of breast cancer. However, obstacles persist, such as dealing with high-dimensional data and the risk of overfitting, necessitating fresh approaches to improve accuracy and real-world applicability.
Methods
In response to these challenges, we propose BCED-Net, which stands for Breast Cancer Ensemble Diagnosis Network. This innovative framework leverages transfer learning and the extreme gradient boosting (XGBoost) classifier on the Breast Cancer RSNA dataset. Our methodology involved feature extraction using pre-trained models—namely, Resnet50, EfficientnetB3, VGG19, Densenet121, and ConvNeXtTiny—followed by the concatenation of the extracted features. Our most promising configuration combined features extracted from deep convolutional neural networks—namely Resnet50, EfficientnetB3, and ConvNeXtTiny—that were classified using the XGBoost classifier.
Results
The ensemble approach demonstrated strong overall performance with an accuracy of 0.89. The precision, recall, and F1-score values, which were all at 0.86, highlight a balanced trade-off between correctly identified positive instances and the ability to capture all actual positive samples.
Conclusion
BCED-Net represents a significant leap forward in addressing persistent issues such as the high dimensionality of features and the risk of overfitting.

Predicting 5-Year Survival Status of Patients with Breast Cancer based on Supervised Wavelet Method: Maryam Farhadian, Hossein Mahjub, Jalal Poorolajal, Abbas Moghimbeigi, Muharram Mansoorizadeh; Osong Public Health Res Perspect. 2014;5(6):324-332. Published online December 31, 2014; DOI: https://doi.org/10.1016/j.phrp.2014.09.002

3,570 View
21 Download
4 Crossref

Objectives
Classification of breast cancer patients into different risk classes is very important in clinical applications. It is estimated that the advent of high-dimensional gene expression data could improve patient classification. In this study, a new method for transforming the high-dimensional gene expression data in a low-dimensional space based on wavelet transform (WT) is presented.
Methods
The proposed method was applied to three publicly available microarray data sets. After dimensionality reduction using supervised wavelet, a predictive support vector machine (SVM) model was built upon the reduced dimensional space. In addition, the proposed method was compared with the supervised principal component analysis (PCA).
Results
The performance of supervised wavelet and supervised PCA based on selected genes were better than the signature genes identified in the other studies. Furthermore, the supervised wavelet method generally performed better than the supervised PCA for predicting the 5-year survival status of patients with breast cancer based on microarray data. In addition, the proposed method had a relatively acceptable performance compared with the other studies.
Conclusion
The results suggest the possibility of developing a new tool using wavelets for the dimension reduction of microarray data sets in the classification framework.

Citations

Citations to this article as recorded by

Diagnosing thyroid disorders: Comparison of logistic regression and neural network models
Shiva Borzouei, Hossein Mahjub, NegarAsaad Sajadi, Maryam Farhadian
Journal of Family Medicine and Primary Care.2020; 9(3): 1470. CrossRef
Thyroid disorder diagnosis based on Mamdani fuzzy inference system classifier
Negar Asaad Sajadi, Hossein Mahjub, Shiva Borzouei, Maryam Farhadian
Koomesh Journal.2020; 22(1): 107. CrossRef
Diagnosis of hypothyroidism using a fuzzy rule-based expert system
Negar Asaad Sajadi, Shiva Borzouei, Hossein Mahjub, Maryam Farhadian
Clinical Epidemiology and Global Health.2019; 7(4): 519. CrossRef
WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis
Kui Deng, Fan Zhang, Qilong Tan, Yue Huang, Wei Song, Zhiwei Rong, Zheng-Jiang Zhu, Kang Li, Zhenzi Li
Analytica Chimica Acta.2019; 1061: 60. CrossRef

Exposure to Dichlorodiphenyltrichloroethane and the Risk of Breast Cancer: A Systematic Review and Meta-analysis: Jae-Hong Park, Eun Shil Cha, Yousun Ko, Myung-Sil Hwang, Jin-Hwan Hong, Won Jin Lee; Osong Public Health Res Perspect. 2014;5(2):77-84. Published online April 30, 2014; DOI: https://doi.org/10.1016/j.phrp.2014.02.001

4,441 View
29 Download
26 Crossref

Abstract PDF

Objectives
This study extended and updated a meta-analysis of the association between exposure to dichlorodiphenyltrichloroethane (DDT) and the risk of breast cancer.
Methods
We reviewed the published literature on exposure to DDE and breast cancer risk to update a meta-analysis from 2004. The total of 35 studies included 16 hospital-based case–control studies, 11 population-based case–control studies, and 10 nested case–control studies identified through keyword searches in the PubMed and EMBASE databases.
Results
The summary odds ratio (OR) for the identified studies was 1.03 (95% confidence interval 0.95–1.12) and the overall heterogeneity in the OR was observed (I² = 40.9; p = 0.006). Subgroup meta-analyses indicated no significant association between exposure to DDE and breast cancer risk by the type of design, study years, biological specimen, and geographical region of the study, except from population-based case–control studies with estimated DDE levels in serum published in 1990s.
Conclusion
Existing studies do not support the view that DDE increases the risk of breast cancer in humans. However, further studies incorporating more detailed information on DDT exposure and other potential risk factors for breast cancer are needed.

Citations

Citations to this article as recorded by

Causes and Risk Factors of Breast Cancer, What Do We Know for Sure? An Evidence Synthesis of Systematic Reviews and Meta-Analyses
Borghild Løyland, Ida Hellum Sandbekken, Ellen Karine Grov, Inger Utne
Cancers.2024; 16(8): 1583. CrossRef
Breast cancer immunophenotypes and serum organochlorine pesticides in Mexican women: Mixture exposure approach
Rodrigo Ugalde-Resano, Ángel Mérida-Ortega, Mariano E. Cebrián, Lizbeth López-Carrillo
Environmental Pollution.2024; 358: 124495. CrossRef
Non-genetic factors and breast cancer: an umbrella review of meta-analyses
Anneza Yiallourou, Katerina Pantavou, Georgios Markozannes, Antonis Pilavas, Andrea Georgiou, Andria Hadjikou, Mary Economou, Neophytos Christodoulou, Konstantinos Letsos, Elina Khattab, Chrystalleni Kossyva, Maria Constantinou, Melanie Theodoridou, Danie
BMC Cancer.2024;[Epub] CrossRef
Validation and green profile assessment of a binary solvent liquid phase microextraction method for the determination of chlorbenside and fenobucarb in lake and wastewater samples by GC–MS
Dotse Selali Chormey
Environmental Science and Pollution Research.2023; 30(15): 44697. CrossRef
Putative interactions between transthyretin and endosulfan II and its relevance in breast cancer
Saurabh Sharma, Lakshay Malhotra, Paromita Mukherjee, Navneet Kaur, Thammineni Krishanlata, Chittur V. Srikanth, Vandana Mishra, Basu Dev Banerjee, Abdul Samath Ethayathulla, Radhey Shyam Sharma
International Journal of Biological Macromolecules.2023; 235: 123670. CrossRef
Exposure to Organochlorine Pesticides and Female Breast Cancer Risk According to Molecular Receptors Expression: a Systematic Review and Meta-analysis of Epidemiological Evidence
Rodrigo Ugalde-Resano, Brenda Gamboa-Loira, Ángel Mérida-Ortega, Alma Rincón-Rubio, Gisela Flores-Collado, Maricela Piña-Pozas, Lizbeth López-Carrillo
Current Environmental Health Reports.2023; 10(4): 442. CrossRef
Mosquito control exposures and breast cancer risk: analysis of 1071 cases and 2096 controls from the Ghana Breast Health Study
Naomie Olivos, Jim E. Banta, Rhonda Spencer-Hwang, Daniel Ansong, Laura E. Beane Freeman, Joe-Nat Clegg-Lamptey, Beatrice Wiafe-Addai, Lawrence Edusei, Ernest Adjei, Nicholas Titiloye, Florence Dedey, Francis Aitpillah, Joseph Oppong, Verna Vanderpuye, Er
Breast Cancer Research.2023;[Epub] CrossRef
Endocrine disrupting chemicals and breast cancer: a systematic review of epidemiological studies
Murphy Lam Yim Wan, Vanessa Anna Co, Hani El-Nezami
Critical Reviews in Food Science and Nutrition.2022; 62(24): 6549. CrossRef
Epidemiology beyond its limits
Lauren E. McCullough, Maret L. Maliniak, Avnika B. Amin, Julia M. Baker, Davit Baliashvili, Julie Barberio, Chloe M. Barrera, Carolyn A. Brown, Lindsay J. Collin, Alexa A. Freedman, David C. Gibbs, Maryam B. Haddad, Eric W. Hall, Sarah Hamid, Kristin R. V
Science Advances.2022;[Epub] CrossRef
Plasma concentrations of chlorinated persistent organic pollutants and their predictors in the general population of Algiers, Algeria
El Hadia Mansouri, Mohamed Reggabi
Emerging Contaminants.2021; 7: 35. CrossRef
Association between type 2 diabetes and exposure to chlorinated persistent organic pollutants in Algeria: A case-control study
El Hadia Mansouri, Mohamed Reggabi
Chemosphere.2021; 264: 128596. CrossRef
Extraction of Chlorobenzenes and PCBs from Water by ZnO Nanoparticles
Yuntao Zhang, Ran Chen, Jim E. Riviere, Jeffrey Comer
Processes.2021; 9(10): 1764. CrossRef
Two Cases of Possible Familial Chronic Myeloid Leukemia in a Family with Extensive History of Cancer
Marisa J.L. Aitken, Christopher B. Benton, Ghayas C. Issa, Koji Sasaki, Musa Yilmaz, Nicholas J. Short
Acta Haematologica.2021; 144(5): 585. CrossRef
In utero DDT exposure and breast density before age 50
Nickilou Y. Krigbaum, Piera M. Cirillo, Julie D. Flom, Jasmine A. McDonald, Mary Beth Terry, Barbara A. Cohn
Reproductive Toxicology.2020; 92: 85. CrossRef
DDT exposure during pregnancy and DNA methylation alterations in female offspring in the Child Health and Development Study
Hui-Chen Wu, Barbara A. Cohn, Piera M. Cirillo, Regina M. Santella, Mary Beth Terry
Reproductive Toxicology.2020; 92: 138. CrossRef
Prediagnostic serum concentrations of organochlorine pesticides and non-Hodgkin lymphoma: A nested case–control study in the Norwegian Janus Serum Bank Cohort
Dazhe Chen, Tom K. Grimsrud, Hilde Langseth, Dana B. Barr, Bryan A. Bassig, Aaron Blair, Kenneth P. Cantor, Marilie D. Gammon, Qing Lan, Nathaniel Rothman, Lawrence S. Engel
Environmental Research.2020; 187: 109515. CrossRef
Global trends in pesticides: A looming threat and viable alternatives
Akanksha Sharma, Ananya Shukla, Kriti Attri, Megha Kumar, Puneet Kumar, Ashish Suttee, Gurpal Singh, Ravi Pratap Barnwal, Neha Singla
Ecotoxicology and Environmental Safety.2020; 201: 110812. CrossRef
Exposure to Endocrine Disrupting Chemicals and Risk of Breast Cancer
Louisane Eve, Béatrice Fervers, Muriel Le Romancer, Nelly Etienne-Selloum
International Journal of Molecular Sciences.2020; 21(23): 9139. CrossRef
Breast Cancer and Exposure to Organochlorines in the CECILE Study: Associations with Plasma Levels Measured at the Time of Diagnosis and Estimated during Adolescence
Delphine Bachelet, Marc-André Verner, Monica Neri, Émilie Cordina Duverger, Corinne Charlier, Patrick Arveux, Sami Haddad, Pascal Guénel
International Journal of Environmental Research an.2019; 16(2): 271. CrossRef
Risk of breast cancer and adipose tissue concentrations of polychlorinated biphenyls and organochlorine pesticides: a hospital-based case-control study in Chinese women
Wenlong Huang, Yuanfang He, Jiefeng Xiao, Yuanni Huang, Anna Li, Meirong He, Kusheng Wu
Environmental Science and Pollution Research.2019; 26(31): 32128. CrossRef
Serum levels of Organochlorine Pesticides and Breast Cancer Risk in Iranian Women
Parisa Paydar, Gholamreza Asadikaram, Hossein Fallah, Hamid Zeynali Nejad, Hamed Akbari, Moslem Abolhassani, Vahid Moazed, Payam Khazaeli, Mahmoud Reza Heidari
Archives of Environmental Contamination and Toxico.2019; 77(4): 480. CrossRef
DDT exposure in early childhood and female breast cancer: Evidence from an ecological study in Taiwan
Simon Chang, Sonia El-Zaemey, Jane Heyworth, Meng-chi Tang
Environment International.2018; 121: 1106. CrossRef
Chiral pharmaceuticals: Environment sources, potential human health impacts, remediation technologies and future perspective
Yaoyu Zhou, Shikang Wu, Hao Zhou, Hongli Huang, Jia Zhao, Yaocheng Deng, Hua Wang, Yuan Yang, Jian Yang, Lin Luo
Environment International.2018; 121: 523. CrossRef
Organochlorine pesticides accumulation and breast cancer: A hospital-based case–control study
Ting-Ting He, An-Jun Zuo, Ji-Gang Wang, Peng Zhao
Tumor Biology.2017; 39(5): 101042831769911. CrossRef
Correlation between toxic organochlorine pesticides and breast cancer
SA Eldakroory, DA El Morsi, RH Abdel-Rahman, S Roshdy, MS Gouida, EO Khashaba
Human & Experimental Toxicology.2017; 36(12): 1326. CrossRef
Breast cancer and persistent organic pollutants (excluding DDT): a systematic literature review
Tafzila Akter Mouly, Leisa-Maree Leontjew Toms
Environmental Science and Pollution Research.2016; 23(22): 22385. CrossRef

Comparison of Breast Cancer Screening Results in Korean Middle-Aged Women: A Hospital-based Prospective Cohort Study: TaeBum Lee; Osong Public Health Res Perspect. 2013;4(4):197-202. Published online August 31, 2013; DOI: https://doi.org/10.1016/j.phrp.2013.06.002

3,677 View
23 Download
5 Crossref

Abstract PDF

Objectives
The aim of this hospital-based prospective study was to evaluate the diagnostic ability of breast cancer screening in Korean middle-aged women using age, ultrasonography, mammography, and magnification mammography, which are commonly used in most hospitals.
Methods
A total of 21 patents were examined using ultrasonography, mammography, and magnification mammography, and their data were prospectively analyzed from August 2011 to March 2013. All patients were divided into benign and malignant groups and the screening results were classified using the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS). The final pathology report was used as the reference standard and the sensitivity and specificity of ultrasonography, mammography, and magnification mammography were evaluated using receiver-operating characteristics (ROC) analysis.
Results
The analysis included 21 patients who underwent biopsy. Among them, three (14.3%) were positive and 18 (85.7%) negative for breast cancer. The average age was 50.5 years (range = 38–61 years). The sensitivity was the same for ultrasonography and magnification mammography and the specificity of magnification mammography was higher than that of ultrasonography. The highest area under the ROC curve (AUC) was observed in the combination of age and magnification mammography (1.000) and the decreasing order of AUC in others was magnification mammography (0.833), ultrasonography (0.787), mammography (0.667), and age (0.648).
Conclusions
In Korean women, the diagnostic accuracy of magnification mammography was better than that of ultrasonography and mammography. The combination of age and magnification mammography increased the sensitivity and diagnostic accuracy.

Citations

Citations to this article as recorded by

Breast cancer in India: Present scenario and the challenges ahead
Ravi Mehrotra, Kavita Yadav
World Journal of Clinical Oncology.2022; 13(3): 209. CrossRef
Integrating age, BMI, and serum N-glycans detected by MALDI mass spectrometry to classify suspicious mammogram findings as benign lesions or breast cancer
Calvin R. K. Blaschke, Elizabeth G. Hill, Anand S. Mehta, Peggi M. Angel, Christine Laronga, Richard R. Drake
Scientific Reports.2022;[Epub] CrossRef
Breast cancer diagnosis by analysis of serum N-glycans using MALDI-TOF mass spectroscopy
Sae Byul Lee, Shambhunath Bose, Sei Hyun Ahn, Byung Ho Son, Beom Seok Ko, Hee Jeong Kim, Il Yong Chung, Jisun Kim, Woochang Lee, Myung-Su Ko, Kyungsoo Lee, Suhwan Chang, Hyoung Soon Park, Jong Won Lee, Dong-Chan Kim, Anna Halama
PLOS ONE.2020; 15(4): e0231004. CrossRef
Recommendations for screening and early detection of common cancers in India
Preetha Rajaraman, Benjamin O Anderson, Partha Basu, Jerome L Belinson, Anil D' Cruz, Preet K Dhillon, Prakash Gupta, Tenkasi S Jawahar, Niranjan Joshi, Uma Kailash, Sharon Kapambwe, Vishwa Mohan Katoch, Suneeta Krishnan, Dharitri Panda, R Sankaranarayana
The Lancet Oncology.2015; 16(7): e352. CrossRef
Predicting 5-Year Survival Status of Patients with Breast Cancer based on Supervised Wavelet Method
Maryam Farhadian, Hossein Mahjub, Jalal Poorolajal, Abbas Moghimbeigi, Muharram Mansoorizadeh
Osong Public Health and Research Perspectives.2014; 5(6): 324. CrossRef

First
Prev
Page of 1
Next
Last

Search