AI Medical Compendium Topic

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Breast Neoplasms

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Attention-based Fusion Network for Breast Cancer Segmentation and Classification Using Multi-modal Ultrasound Images.

Ultrasound in medicine & biology
OBJECTIVE: Breast cancer is one of the most commonly occurring cancers in women. Thus, early detection and treatment of cancer lead to a better outcome for the patient. Ultrasound (US) imaging plays a crucial role in the early detection of breast can...

Freeze-Thaw-Induced Patterning of Extracellular Vesicles with Artificial Intelligence for Breast Cancers Identifications.

Small (Weinheim an der Bergstrasse, Germany)
Extracellular vesicles (EVs) play a crucial role in the occurrence and progression of cancer. The efficient isolation and analysis of EVs for early cancer diagnosis and prognosis have gained significant attention. In this study, for the first time, a...

Predicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model.

Frontiers in immunology
OBJECTIVE: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast c...

Artificial intelligence improves mammography-based breast cancer risk prediction.

Trends in cancer
Artificial intelligence (AI) is enabling us to delve deeply into the information inherent in a mammogram and identify novel features associated with high risk of a future breast cancer diagnosis. Here, we discuss how AI is improving mammographic dens...

CNN-Based Cross-Modality Fusion for Enhanced Breast Cancer Detection Using Mammography and Ultrasound.

Tomography (Ann Arbor, Mich.)
Breast cancer is a leading cause of mortality among women in Taiwan and globally. Non-invasive imaging methods, such as mammography and ultrasound, are critical for early detection, yet standalone modalities have limitations in regard to their diagn...

Novel models based on machine learning to predict the prognosis of metaplastic breast cancer.

Breast (Edinburgh, Scotland)
BACKGROUND: Metaplastic breast cancer (MBC) is a rare and highly aggressive histological subtype of breast cancer. There remains a significant lack of precise predictive models available for use in clinical practice.

Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.

BMC cancer
BACKGROUND: In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 pr...

BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI.

PloS one
Development of artificial intelligence (AI) for medical imaging demands curation and cleaning of large-scale clinical datasets comprising hundreds of thousands of images. Some modalities, such as mammography, contain highly standardized imaging. In c...

Establishment of multiple machine learning prognostic model for gene differences between primary tumors and lymph nodes in luminal breast cancer.

Breast cancer research and treatment
BACKGROUND: This study aimed to explore the correlation between primary tumors (PT) and paired metastatic lymph nodes (LN) and to develop a predictive model to provide evidence for forecasting patient prognoses.