5 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.

The invention discloses a chyloleakage condition detection device in a neck lymph node cleaning operation, and relates to the technical field of medical supplies, the chyloleakage condition detection device comprises a bottom plate, and the upper side of the bottom plate is provided with a shell. According to the device for detecting the chyloleakage condition in the neck lymph node cleaning operation, liquid to be detected is actively sucked into the device through the negative pressure effect of a pressing air bag in the rapid suction and liquid homogenization assembly; the situation that the detection efficiency is reduced due to the fact that traditional detection paper is extracted only through a filter paper material in a slow passive suction mode is avoided, and meanwhile liquid to be detected in a plurality of infusion tubes flows into a plurality of liquid homogenizing grooves correspondingly formed in the upper side of a liquid homogenizing plate through corresponding liquid outlet holes in a mode that an air bag is pressed to increase the pressure intensity; the detection paper is uniformly wetted through the liquid homogenizing tank, so that the problem that the discoloration reaction is not obvious due to non-uniform wetting of the to-be-detected liquid by the traditional detection paper is prevented, and the detection accuracy is ensured.

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.

The invention relates to an application of a reagent for detecting the expression level of a target protein in preparation of an oral squamous cell carcinoma neck lymph node metastasis risk prediction kit and the oral squamous cell carcinoma neck lymph node metastasis risk prediction kit. The key proteins for predicting the risk of oral squamous cell carcinoma neck lymph node metastasis are screened out, the neck metastasis of oral squamous cell carcinoma can be efficiently predicted by detecting the levels of the key proteins, the method has high accuracy and sensitivity, a scientific basis is provided for individualized implementation of neck cleaning and postoperative metastasis early warning mechanisms, and the method is suitable for popularization and application. The oral cancer neck operation complication rate can be reduced, and the survival rate and the life quality can be improved.