In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.
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http://dx.doi.org/10.1007/s10916-011-9762-6 | DOI Listing |
Breast Cancer Res
January 2025
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.
Background: CDK4/6 inhibitors have significantly improved the survival of patients with HR-positive/HER2-negative breast cancer, becoming a first-line treatment option. However, the development of resistance to these inhibitors is inevitable. To address this challenge, novel strategies are required to overcome resistance, necessitating a deeper understanding of its mechanisms.
View Article and Find Full Text PDFBMC Cancer
January 2025
Faculty of Medicine, University of Cologne and Institute for Health Economics and Clinical Epidemiology, University Hospital Cologne, Cologne, Germany.
Background: Patients who actively engage in their medical decision-making processes can experience better health outcomes. This exploratory study aimed to identify predictors of preferred and actual roles in decision-making in healthy women with BRCA1/2 pathogenic variants (PVs).
Methods: Women with BRCA1/2 PVs without a history of breast and/or ovarian cancer were recruited in six centres across Germany.
Invest New Drugs
January 2025
UCD School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
Background: Since MYC is one of the most frequently altered driver genes involved in cancer formation, it is a potential target for new anti-cancer therapies. Historically, however, MYC has proved difficult to target due to the absence of a suitable crevice for binding potential low molecular weight drugs.
Objective: The aim of this study was to evaluate a novel molecular glue, dubbed GT19630, which degrades both MYC and GSPT1, for the treatment of breast cancer.
Radiol Med
January 2025
Department of Translational Medicine, University of Ferrara, Ferrara, Italy.
Purpose: Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on conventional and radiomic signatures extracted from baseline [F]FDG PET/CT.
Material And Methods: Primary tumor and the most significant lymph node metastasis were manually segmented in baseline [F]FDG PET/CT of 52 newly diagnosed BC patients. Clinical parameters, NAC and conventional semiquantitative PET parameters were collected.
EMBO J
January 2025
Department of Geriatrics, Gerontology Institute of Anhui Province, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
mTOR plays a pivotal role in cancer growth control upon amino acid response. Recently, CDK inhibitor P27KIP1 has been reported as a noncanonical inhibitor of mTOR signaling in MEFs, via unclear mechanisms. Here, we find that P27KIP1 degradation via E3 ligase TRIM21 is inhibited by human micropeptide hSPAR through its C-terminus (hSPAR-C), causing P27KIP1's cytoplasmic accumulation in breast cancer cells.
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