AIMC Topic: Lymphatic Metastasis
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Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics.
Nature communications
Sep 23, 2020
Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) mo...
Radiomics for Diagnosing Lateral Pelvic Lymph Nodes in Rectal Cancer: Artificial Intelligence Enabling Precision Medicine?
Annals of surgical oncology
Aug 6, 2020
Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.
PloS one
Aug 5, 2020
OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, ...
Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.
JAMA network open
Jul 1, 2020
IMPORTANCE: Accurate identification of lymph node metastasis preoperatively and noninvasively in patients with cervical cancer can avoid unnecessary surgical intervention and benefit treatment planning.
Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2.
Genomics
Jun 30, 2020
The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to provide valuable information for the identification of potential diagnostic biomarkers and pathological...
Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.
Cancer research and treatment
Jun 30, 2020
PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of SLNs by a pathologist is not easy and is a tedious and...
Automatic detection of cervical lymph nodes in patients with oral squamous cell carcinoma using a deep learning technique: a preliminary study.
Oral radiology
Jun 6, 2020
OBJECTIVE: To apply a deep learning object detection technique to CT images for detecting cervical lymph nodes metastasis in patients with oral cancers, and to clarify the detection performance.
Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.
Scientific reports
May 8, 2020
The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in tracking the progression of the metastatic lymph nodes (mLNs) of patients with papillary thyroid cancer (...
Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.
AJR. American journal of roentgenology
Apr 29, 2020
The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET, the utility of deep machine learning with a convolutional neural network (CNN) in predicting the potential of newly diagnosed non-small cell lung can...
Radiopharmaceuticals
Neoplasm Metastasis
Fluorodeoxyglucose F18
Carcinoma, Non-Small-Cell Lung
Lymphatic Metastasis
Predictive Value of Tests
Positron Emission Tomography Computed Tomography
Humans
Neural Networks, Computer
Retrospective Studies
Female
Male
Middle Aged
Imaging, Three-Dimensional
Lung Neoplasms
Aged
Aged, 80 and over
Adult
Sensitivity and Specificity
A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.
Lung cancer (Amsterdam, Netherlands)
Apr 25, 2020
OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the ...
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