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Breast Neoplasms

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PViT-AIR: Puzzling vision transformer-based affine image registration for multi histopathology and faxitron images of breast tissue.

Medical image analysis
Breast cancer is a significant global public health concern, with various treatment options available based on tumor characteristics. Pathological examination of excision specimens after surgery provides essential information for treatment decisions....

Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer.

BMC cancer
BACKGROUND: With the development of novel anti-HER2 targeted drugs, such as ADCs, it has become increasingly important to accurately interpret HER2 expression in breast cancer. Previous studies have demonstrated high intra-observer and inter-observer...

Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients.

eLife
BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous studies suggest that lipids may play a role in CIPN. Therefore, the present study aimed to identify th...

Predictive model of prognosis index for invasive micropapillary carcinoma of the breast based on machine learning: a SEER population-based study.

BMC medical informatics and decision making
BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer. Its epidemiological features, treatment principles, and prognostic factors remain controversial.

Feature-based detection of breast cancer using convolutional neural network and feature engineering.

Scientific reports
Breast cancer (BC) is a prominent cause of female mortality on a global scale. Recently, there has been growing interest in utilizing blood and tissue-based biomarkers to detect and diagnose BC, as this method offers a non-invasive approach. To impro...

Developing machine learning models for personalized treatment strategies in early breast cancer patients undergoing neoadjuvant systemic therapy based on SEER database.

Scientific reports
This study aimed to compare the long-term outcomes of breast-conserving surgery plus radiotherapy (BCS + RT) and mastectomy in early breast cancer (EBC) patients who received neoadjuvant systemic therapy (NST), and sought to construct and authenticat...

Detection of breast cancer in digital breast tomosynthesis with vision transformers.

Scientific reports
Digital Breast Tomosynthesis (DBT) has revolutionized more traditional breast imaging through its three-dimensional (3D) visualization capability that significantly enhances lesion discernibility, reduces tissue overlap, and improves diagnostic preci...

Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study.

JMIR medical informatics
BACKGROUND: Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse ...

From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management.

Sensors (Basel, Switzerland)
Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than one-third of all cancer cases affecting women. It causes aberrant cell development, which can assault or spread to other sections of the body, perhaps l...

Deep learning applications in breast cancer histopathological imaging: diagnosis, treatment, and prognosis.

Breast cancer research : BCR
Breast cancer is the most common malignant tumor among women worldwide and remains one of the leading causes of death among women. Its incidence and mortality rates are continuously rising. In recent years, with the rapid advancement of deep learning...