AIMC Topic: Lymphatic Metastasis

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Interpretable classification of pathology whole-slide images using attention based context-aware graph convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Whole slide image (WSI) classification and lesion localization within giga-pixel slide are challenging tasks in computational pathology that requires context-aware representations of histological features to adequately infer...

Deep learning radiomics of ultrasonography for comprehensively predicting tumor and axillary lymph node status after neoadjuvant chemotherapy in breast cancer patients: A multicenter study.

Cancer
BACKGROUND: Neoadjuvant chemotherapy (NAC) can downstage tumors and axillary lymph nodes in breast cancer (BC) patients. However, tumors and axillary response to NAC are not parallel and vary among patients. This study aims to explore the feasibility...

Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate identification of axillary lymph node (ALN) status in breast cancer patients is important for determining treatment options and avoiding axillary overtreatments. Our study aims to comprehensively compare the perform...

Exploring risk factors for cervical lymph node metastasis in papillary thyroid microcarcinoma: construction of a novel population-based predictive model.

BMC endocrine disorders
BACKGROUND: Machine learning was a highly effective tool in model construction. We aim to establish a machine learning-based predictive model for predicting the cervical lymph node metastasis (LNM) in papillary thyroid microcarcinoma (PTMC).

Intraoperative near-infrared lymphography with indocyanine green may aid lymph node dissection during robot-assisted resection of gastroesophageal junction cancer.

Surgical endoscopy
BACKGROUND: Adequate lymphadenectomy during gastroesophageal junction (GEJ) cancer resection is essential, because lymph node (LN) metastasis correlates with increased recurrence risk. Fluorescence lymphography with indocyanine green (ICG) has been u...

Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear.

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

BioMed research international
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...

Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer.

Cancer research and treatment
PURPOSE: Assessing the metastasis status of the sentinel lymph nodes (SLNs) for hematoxylin and eosin-stained frozen tissue sections by pathologists is an essential but tedious and time-consuming task that contributes to accurate breast cancer stagin...