AIMC Topic: Lymph Nodes
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Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: a large-scale pan-cancer cohort, machine learning and experimental study: Retraction.
International journal of surgery (London, England)
Sep 1, 2024
An unsupervised learning model based on CT radiomics features accurately predicts axillary lymph node metastasis in breast cancer patients: diagnostic study.
International journal of surgery (London, England)
Sep 1, 2024
BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axillary lymph nodes (ALNs) is unsatisfactory. In this study, the authors propose the use of radiomic technology and three-dimensional (3D) visualization ...
Prediction model for lateral lymph node metastasis of papillary thyroid carcinoma in children and adolescents based on ultrasound imaging and clinical features: a retrospective study.
BMC medical imaging
Aug 29, 2024
BACKGROUND: The presence of lateral lymph node metastases (LNM) in paediatric patients with papillary thyroid cancer (PTC) is an independent risk factor for recurrence. We aimed to identify risk factors and establish a prediction model for lateral LN...
Adolescent
Thyroid Neoplasms
Ultrasonography
Humans
ROC Curve
Retrospective Studies
Thyroid Cancer, Papillary
Lymph Nodes
Female
Predictive Learning Models
Risk Factors
Lymphatic Metastasis
Young Adult
Regression Analysis
Male
Predictive Value of Tests
Risk Assessment
Area Under Curve
Reference Values
Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy.
Academic radiology
Aug 24, 2024
RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics nomogram (DLRN) for predicting tumor status and axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy (NAC) in patients with breast can...
Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study.
Journal of magnetic resonance imaging : JMRI
Aug 22, 2024
BACKGROUND: Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized select...
Peritumoral edema enhances MRI-based deep learning radiomic model for axillary lymph node metastasis burden prediction in breast cancer.
Scientific reports
Aug 14, 2024
To investigate whether peritumoral edema (PE) could enhance deep learning radiomic (DLR) model in predicting axillary lymph node metastasis (ALNM) burden in breast cancer. Invasive breast cancer patients with preoperative MRI were retrospectively enr...
Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.
Breast (Edinburgh, Scotland)
Aug 9, 2024
PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise meth...
Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.
Academic radiology
Aug 5, 2024
RATIONALE AND OBJECTIVES: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established ...
MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.
International journal of surgery (London, England)
Aug 1, 2024
INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to...
Artificial Intelligence to Predict the Risk of Lymph Node Metastasis in T2 Colorectal Cancer.
Annals of surgery
Jul 30, 2024
OBJECTIVE: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC).
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