AIMC Topic: Breast Neoplasms

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Impact of Gene Biomarker Discovery Tools Based on Protein-Protein Interaction and Machine Learning on Performance of Artificial Intelligence Models in Predicting Clinical Stages of Breast Cancer.

Interdisciplinary sciences, computational life sciences
Breast cancer, as one of the most common diseases threatening the women's life, has attracted serious attention of the clinical and biomedical researchers worldwide. The genome-based studies along with their registered GEO datasets are frequent in th...

Mammographic image classification with deep fusion learning.

Scientific reports
To better address the recognition of abnormalities among mammographic images, in this study we apply the deep fusion learning approach based on Pre-trained models to discover the discriminative patterns between Normal and Tumor categories. We designe...

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to growing demands for rapid and accurate diagnostic reporting. In modern breast imaging centers, full-fiel...

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text.

BMC medical informatics and decision making
BACKGROUNDS: Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by differe...

Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging.

Contrast media & molecular imaging
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications includin...

White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Bayesian network is a probabilistic model of which the prediction accuracy may not be one of the highest in the machine learning family. Deep learning (DL) on the other hand possess of higher predictive power than many other...

Spectral-Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification.

Sensors (Basel, Switzerland)
Cancer identification and classification from histopathological images of the breast depends greatly on experts, and computer-aided diagnosis can play an important role in disagreement of experts. This automatic process has increased the accuracy of ...

Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer.

Scientific reports
Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC...