AIMC Topic: Lymph Nodes
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MRI Radiomics of Breast Cancer: Machine Learning-Based Prediction of Lymphovascular Invasion Status.
Academic radiology
Dec 4, 2021
RATIONALE AND OBJECTIVES: In patients with breast cancer (BC), lymphovascular invasion (LVI) status is considered an important prognostic factor. We aimed to develop machine learning (ML)-based radiomics models for the prediction of LVI status in pat...
Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?
Gynecologic oncology
Nov 15, 2021
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...
Deep learning can predict lymph node status directly from histology in colorectal cancer.
European journal of cancer (Oxford, England : 1990)
Oct 11, 2021
BACKGROUND: Lymph node status is a prognostic marker and strongly influences therapeutic decisions in colorectal cancer (CRC).
Few-Shot Breast Cancer Metastases Classification via Unsupervised Cell Ranking.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Tumor metastases detection is of great importance for the treatment of breast cancer patients. Various CNN (convolutional neural network) based methods get excellent performance in object detection/segmentation. However, the detection of metastases i...
Transhiatal robot-assisted minimally invasive esophagectomy: unclear benefits compared to traditional transhiatal esophagectomy.
Journal of robotic surgery
Sep 28, 2021
Esophagectomy is a high-risk operation, regardless of technique. Minimally invasive transthoracic esophagectomy could reduce length of stay and pulmonary complications compared to traditional open approaches, but the benefits of minimally invasive tr...
Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis.
BMC cancer
Sep 26, 2021
BACKGROUND: Artificial intelligence (AI) is increasingly being used in medical imaging analysis. We aimed to evaluate the diagnostic accuracy of AI models used for detection of lymph node metastasis on pre-operative staging imaging for colorectal can...
An [18F]FDG-PET/CT deep learning method for fully automated detection of pathological mediastinal lymph nodes in lung cancer patients.
European journal of nuclear medicine and molecular imaging
Sep 14, 2021
PURPOSE: The identification of pathological mediastinal lymph nodes is an important step in the staging of lung cancer, with the presence of metastases significantly affecting survival rates. Nodes are currently identified by a physician, but this pr...
Assessment of Axillary Lymph Nodes for Metastasis on Ultrasound Using Artificial Intelligence.
Ultrasonic imaging
Aug 20, 2021
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
Aug 5, 2021
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
Jul 29, 2021
BACKGROUND: da Vinci robot-assisted axillary lymph node dissection (dVALND) can be a minimally invasive technique to minimize post-operative complications.
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