3 results about "Cervical lymph nodes" patented technology

The application discloses a thyroid cancer and neck lymph node metastasis risk assessment method, relates to the cross technical field of bioinformatics and metabolomics, and mainly comprises the following steps: converting single-cell metabolomics signals into a metabolic feature matrix with cells as rows and metabolites as columns, constructing a patient-level metabolic dataset based on patient identification information, preprocessing the patient-level metabolic dataset to obtain a preprocessed patient-level metabolic dataset, screening features to obtain key metabolic features, and performing hierarchical summary prediction to obtain individual risk assessment results. The thyroid cancer and neck lymph node metastasis risk assessment method can non-invasively and accurately predict the risk of thyroid cancer and neck lymph node metastasis.

This invention discloses a multi-scale feature fusion-based cervical lymph node identification system for cancer metastasis, relating to the fields of artificial intelligence and ultrasound image analysis. It includes three sets of encoded neural networks, two feature enhancement modules, a dual attention module, and a decoding module. The multi-scale feature fusion network can extract lymph node features from different viewpoints and fuse features from different viewpoints. The dual attention module controls the information flow between low-level and high-level features by generating descriptive factors, selecting useful feature channels and avoiding the adverse effects of useless channel information on the model output, resulting in finer localization contours and more accurate diagnosis. This system can locate lymph nodes on cervical ultrasound images and identify lymph nodes with cancer metastasis, thus better assisting doctors in quickly identifying and diagnosing cervical lymph nodes during ultrasound examinations, avoiding excessive subjective factors, and making the diagnostic results more reliable.

This invention relates to the field of medical data processing technology, specifically to a method and system for constructing a cervical metastasis prediction model for T1 stage oral squamous cell carcinoma. Addressing the problems of existing technologies, such as the difficulty in accurately assessing the risk of occult lymph node metastasis in T1 stage patients preoperatively, the decreased discrimination and calibration of existing models due to mixed staging, and the lack of intuitive and usable tools, this application constructs a cervical metastasis prediction model for T1 stage oral squamous cell carcinoma. The specific construction method is as follows: Obtaining the subject's characteristic data; using the occurrence of cervical lymph node metastasis as the dependent variable, performing univariate logistic regression analysis on the independent variables of the characteristic data to determine candidate risk factors; performing multivariate logistic regression analysis on the obtained candidate risk factors to screen independent predictive factors; constructing a nomogram based on the independent predictive factors, and predicting the risk of cervical lymph node metastasis in T1 stage oral squamous cell carcinoma patients based on the nomogram.