OBJECTIVES: This study aims to develop and validate machine learning-based diagnostic and prognostic models to predict the risk of distant lymph node metastases (DLNM) in patients with hepatocellular carcinoma (HCC) and to evaluate the prognosis for ...
The journal of pathology. Clinical research
Sep 1, 2024
Researchers have attempted to identify the factors involved in lymph node recurrence in cT1-2N0 tongue squamous cell carcinoma (SCC). However, studies combining histopathological and clinicopathological information in prediction models are limited. W...
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Jul 20, 2024
OBJECTIVE: To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyroid tumors in patients with Hashimoto's thyroiditis (HT) combined with papillary thyroid carcinoma (PTC) using machine learning (ML) models, and to ex...
BACKGROUND: The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate the risk factors for lateral lymph node metastasis and develop machine learning models combining thes...
BACKGROUND: For medullary thyroid carcinoma (MTC) with no positive findings in the lateral neck before surgery, whether prophylactic lateral neck dissection (LND) is needed remains controversial. A better way to predict occult metastasis in the later...
PURPOSE: Natural language understanding (NLU) may be particularly well equipped for enhanced data capture from the electronic health record given its examination of both content-driven and context-driven extraction.
BACKGROUND: Risk evaluation of lymph node metastasis for early-stage (T1 and T2) colorectal cancers is critical for determining therapeutic strategies. Traditional methods of lymph node metastasis prediction have limited accuracy. This systematic rev...
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: The main metastatic route for lung cancer is lymph node metastasis, and studies have shown that non-small cell lung cancer (NSCLC) has a high risk of lymph node infiltration.
OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes.