M. Karoui, R. Kamoun, H. Nefzi, N. Marrakchi, H. Raies, A. Mezlini, K. Meddeb, F. Ellouze

Psycho-Oncologie, Vol.17, No.1, pp. 31-37, 2023, DOI:10.3166/pson-2022-0211

Abstract Aim: The objective of this study is to investigate the prevalence of depression and anxiety in women Tunisian population followed for breast cancer and to identify the socio-demographic, clinical, and of couple relationship factors associated with them.
Procedure: Cross-sectional study on 100 patients followed for confirmed breast cancer. A questionnaire on the sociodemographic, clinical, therapeutic, conjugal, and sexual characteristics of the couple was completed. The HADS (Hospital Anxiety and Depression Scale) was used for the detection of anxiety and depressive symptoms.
Results: A clinical score was found in 48% of cases for anxiety and 37% of cases for depression. Patients… More >

Alia Alshehri, Duaa AlSaeed^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 939-970, 2023, DOI:10.32604/iasc.2023.037096

Abstract One of the most prevalent cancers in women is breast cancer. Early and accurate detection can decrease the mortality rate associated with breast cancer. Governments and health organizations emphasize the significance of early breast cancer screening since it is associated to a greater variety of available treatments and a higher chance of survival. Patients have the best chance of obtaining effective treatment when they are diagnosed early. The detection and diagnosis of breast cancer have involved using various image types and imaging modalities. Breast “infrared thermal” imaging is one of the imaging modalities., a screening instrument used to measure the… More >

E. Jenifer Sweetlin^*, S. Saudia

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 343-367, 2023, DOI:10.32604/iasc.2023.036742

Abstract This paper proposes a hybrid feature selection sequence complemented with filter and wrapper concepts to improve the accuracy of Machine Learning (ML) based supervised classifiers for classifying the survivability of breast cancer patients into classes, living and deceased using METABRIC and Surveillance, Epidemiology and End Results (SEER) datasets. The ML-based classifiers used in the analysis are: Multiple Logistic Regression, K-Nearest Neighbors, Decision Tree, Random Forest, Support Vector Machine and Multilayer Perceptron. The workflow of the proposed ML algorithm sequence comprises the following stages: data cleaning, data balancing, feature selection via a filter and wrapper sequence, cross validation-based training, testing and… More >

JINGYUE FU, RUI CHEN, ZHIZHENG ZHANG, JIANYI ZHAO, TIANSONG XIA^*

Oncology Research, Vol.31, No.2, pp. 157-167, 2023, DOI:10.32604/or.2023.027972

Abstract Background: Breast cancer has become the most common malignant tumor in the world. It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer, which causes the disparity in prognosis. Recently, inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer, so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies. Methods: We assessed the connection between Inflammatory-Related Genes (IRGs) and breast cancer by studying the TCGA database.… More > Graphic Abstract

XI YANG^1,5,#, HUIXIAN WU^2,3,#, CHAO XIONG^4,#, BO ZHAO¹, MEILIAN LIU¹, JIE QIN⁶, MEI DENG^1,2,3,*

BIOCELL, Vol.47, No.5, pp. 1021-1037, 2023, DOI:10.32604/biocell.2023.027103

Abstract Background: Cytochrome b561 (CYB561) plays a critical role in neuroendocrine function, cardiovascular regulation, and tumor growth; however, the prognostic value of CYB561 in patients with breast cancer and the relationship between CYB561 expression and immune infiltration in breast cancer remain unclear. Methods: The mRNA expression and clinical data of patients with breast cancer were obtained from The Cancer Genome Atlas database. Functional enrichment analysis was used to explore underlying biological functions associated with CYB561. The methylation status of CYB561 was analyzed using the MethSurv database. The enrichment score of immune cell infiltration for CYB561 in breast cancer was calculated using… More >

Manar Ahmed Hamza^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2879-2895, 2023, DOI:10.32604/iasc.2023.034719

Abstract Breast Cancer (BC) is considered the most commonly scrutinized cancer in women worldwide, affecting one in eight women in a lifetime. Mammography screening becomes one such standard method that is helpful in identifying suspicious masses’ malignancy of BC at an initial level. However, the prior identification of masses in mammograms was still challenging for extremely dense and dense breast categories and needs an effective and automatic mechanisms for helping radiotherapists in diagnosis. Deep learning (DL) techniques were broadly utilized for medical imaging applications, particularly breast mass classification. The advancements in the DL field paved the way for highly intellectual and… More >

Emad Abd Al Rahman¹, Nur Intan Raihana Ruhaiyem^1,*, Majed Bouchahma², Kamarul Imran Musa³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3007-3028, 2023, DOI:10.32604/iasc.2023.032580

Abstract This study offers a framework for a breast cancer computer-aided treatment prediction (CATP) system. The rising death rate among women due to breast cancer is a worldwide health concern that can only be addressed by early diagnosis and frequent screening. Mammography has been the most utilized breast imaging technique to date. Radiologists have begun to use computer-aided detection and diagnosis (CAD) systems to improve the accuracy of breast cancer diagnosis by minimizing human errors. Despite the progress of artificial intelligence (AI) in the medical field, this study indicates that systems that can anticipate a treatment plan once a patient has… More >

A. Selvi^*, S. Thilagamani

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2973-2987, 2023, DOI:10.32604/iasc.2022.029850

Abstract Mammography is considered a significant image for accurate breast cancer detection. Content-based image retrieval (CBIR) contributes to classifying the query mammography image and retrieves similar mammographic images from the database. This CBIR system helps a physician to give better treatment. Local features must be described with the input images to retrieve similar images. Existing methods are inefficient and inaccurate by failing in local features analysis. Hence, efficient digital mammography image retrieval needs to be implemented. This paper proposed reliable recovery of the mammographic image from the database, which requires the removal of noise using Kalman filter and scale-invariant feature transform… More >

Ziquan Zhu, Shui-Hua Wang, Yu-Dong Zhang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2127-2172, 2023, DOI:10.32604/cmes.2023.025484

Abstract Problems: For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women. The data showed that female breast cancer had become one of the most common cancers. Aims: A large number of clinical trials have proved that if breast cancer is diagnosed at an early stage, it could give patients more… More > Graphic Abstract

ZEINAB KLAAB¹, AZIZA HASSAN², JAWAHER ALBAQAMI¹, FAIZAH A. ALMALKI^1,*

BIOCELL, Vol.47, No.4, pp. 891-904, 2023, DOI:10.32604/biocell.2023.026556

Abstract Cancer remains to be one of the most severe sicknesses globally. Cases have kept rising over the years. Breast cancer (BC), which is among the leading types of cancers and predominantly affects women, is the second leading cause of cancer mortality. Researchers have developed interventions over the years; however, the BC survival rate has not improved since the 1980s. This has created the need for novel drug interventions that would manage and treat BC more effectively. This study focused on using a combination of natural product extracts such as phytoestrogen (Ziziphus jujube) and Tannin nanoparticles (NP99) together, which we have… More >