AIMC Topic: Lymphatic Metastasis

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Radiomics analysis combining unsupervised learning and handcrafted features: A multiple-disease study.

Medical physics
PURPOSE: To study and investigate the synergistic benefit of incorporating both conventional handcrafted and learning-based features in disease identification across a wide range of clinical setups.

Artificial intelligence in gynecologic cancers: Current status and future challenges - A systematic review.

Artificial intelligence in medicine
OBJECTIVE: Over the past years, the application of artificial intelligence (AI) in medicine has increased rapidly, especially in diagnostics, and in the near future, the role of AI in medicine will become progressively more important. In this study, ...

Assessment of Axillary Lymph Nodes for Metastasis on Ultrasound Using Artificial Intelligence.

Ultrasonic imaging
The purpose of this study was to evaluate an artificial intelligence (AI) system for the classification of axillary lymph nodes on ultrasound compared to radiologists. Ultrasound images of 317 axillary lymph nodes from patients referred for ultrasoun...

Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning.

Computers in biology and medicine
When doctors use contrast-enhanced computed tomography (CECT) images to predict the metastasis of axillary lymph nodes (ALN) for breast cancer patients, the prediction performance could be degraded by subjective factors such as experience, psychologi...

Efficacy of da Vinci robot-assisted lymph node surgery than conventional axillary lymph node dissection in breast cancer - A comparative study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: da Vinci robot-assisted axillary lymph node dissection (dVALND) can be a minimally invasive technique to minimize post-operative complications.

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

European journal of cancer (Oxford, England : 1990)
AIM: Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metas...

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

Clinical breast cancer
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...

Second-order multi-instance learning model for whole slide image classification.

Physics in medicine and biology
Whole slide histopathology images (WSIs) play a crucial role in diagnosing lymph node metastasis of breast cancer, which usually lack fine-grade annotations of tumor regions and have large resolutions (typically 10 × 10pixels). Multi-instance learnin...

The predictive power of artificial intelligence on mediastinal lymphnode metastasis.

General thoracic and cardiovascular surgery
OBJECTIVE: The aim of this study was to create the preoperative predictive model on mediastinal lymph-node metastasis based on artificial intelligence in surgically resected lung adenocarcinoma.

Dual energy CT image prediction on primary tumor of lung cancer for nodal metastasis using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lymph node metastasis (LNM) identification is the most clinically important tasks related to survival and recurrence from lung cancer. However, the preoperative prediction of nodal metastasis remains a challenge to determine surgical plans and pretre...