OBJECTIVES: Cervical lymph nodes with internal cystic changes are seen with several pathologies, including papillary thyroid carcinoma (PTC), tuberculosis (TB), and HPV-positive oropharyngeal squamous cell carcinoma (HPV+OPSCC). Differentiating these...
Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to automatically extract relevant features from the patient's...
N-staging is a determining factor for prognostic assessment and decision-making for stage-based cancer therapeutic strategies. Visual inspection of whole-slides of intact lymph nodes is currently the main method used by pathologists to calculate the ...
BACKGROUND: Survival rate may be predicted by tumor-node-metastasis staging systems in colon cancer. In clinical practice, about 20 to 30 clinicopathological factors and blood test data have been used. Various predictive factors for recurrence have b...
International journal of radiation oncology, biology, physics
Feb 6, 2021
PURPOSE: Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation therapy. Given the constraints imposed by relatively small sample sizes in real-world medical applica...
PURPOSE: Accurate clinical diagnosis of lymph node metastases is of paramount importance in the treatment of patients with abdominopelvic malignancy. This review assesses the diagnostic performance of deep learning algorithms and radiomics models for...
INTRODUCTION: Previous studies showed suboptimal adherence to clinical practice guidelines for pelvic lymph node dissection (PLND) during radical prostatectomy (RP). Robot-assisted RP (RARP) has become the predominant surgical management for localize...
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Jan 23, 2021
BACKGROUND: Traditional diagnosis methods for lymph node metastases are labor-intensive and time-consuming. As a result, diagnostic systems based on deep learning (DL) algorithms have become a hot topic. However, current research lacks testing with s...
PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely s...