154 results about "Thyroid cancer" patented technology

The invention relates to the field of medical informatization. The invention discloses a thyroid cancer electronic medical record system based on multi-modal data fusion. The thyroid cancer electronic medical record system comprises a multi-modal data acquisition module which acquires patient texts, ultrasonic images, genes, biochemical indexes and clinical data and performs standardized calibration to generate standard data; the multi-modal feature extraction module extracts semantic, structure, mutation, change and fluctuation features of each standard data through multiple technologies; the single-mode prediction model construction module constructs single-mode prediction models of texts, images and the like based on the features and outputs results; and the multi-modal fusion prediction module fuses the single-modal model based on the deep learning framework to output a multi-modal fusion prediction result. According to the invention, multi-modal data are integrated, and the accuracy and comprehensiveness of thyroid cancer diagnosis are improved. The system ensures consistency through standardized data processing, and assists doctors to accurately judge pathological types, recommend therapeutic schedules and evaluate prognosis by means of a multi-modal feature extraction and fusion mechanism.

The invention provides a thyroid cancer auxiliary diagnosis and metastasis risk prediction method based on deep learning, and relates to the technical field of artificial intelligence auxiliary medical treatment, and the method comprises the steps: extracting ultrasonic image multi-scale features through a self-adaptive neural architecture search network, combining clinical examination data, fusing diagnosis and treatment knowledge through a neural symbol inference device, and carrying out the prediction of the metastasis risk. Generating a knowledge enhancement feature map; constructing a feature propagation field by using a dynamic neural field network, solving a dynamic evolution equation, and generating a spatial-temporal feature field representing the dynamic change of focus features; constructing a tumor diffusion kinetic model by using an implicit neural representation network and a nerve ordinary differential equation network, calculating a transition probability based on an optimal transmission algorithm, solving an optimal control equation, and outputting a metastasis risk prediction result of each organ; the thyroid cancer diagnosis accuracy and metastasis risk prediction reliability can be effectively improved, and doctors can be assisted in accurate diagnosis and treatment.

The invention discloses a thyroid cancer pathological image classification method and system based on multi-modal feature fusion and Bayesian optimization, and relates to the technical field of medical image processing, and the method comprises the steps: collecting a thyroid ultrasound image data set, and carrying out the preprocessing operation; extracting an improved local binary pattern feature, a Haralick texture feature and a VGG16 depth feature, and constructing a mixed feature space; and splicing the features in the mixed feature space into a 4119-dimensional mixed feature vector, and carrying out feature importance screening by utilizing ExtraTres. Improved local binary pattern features, Haralick texture features and VGG16 depth features are fused, a mixed feature space is constructed, feature importance screening and PCA dimension reduction are performed by using ExtraTrees, multi-level features of the image are effectively extracted, the accuracy of benign and malignant thyroid nodule classification is remarkably improved, meanwhile, network hyper-parameters are dynamically adjusted through a Bayesian optimization algorithm, and the classification accuracy of benign and malignant thyroid nodules is improved. And model convergence is accelerated in combination with a cosine annealing strategy, so that the generalization ability of the model is enhanced, and the model can be excellently expressed on different data sets.

The invention discloses a thyroid cancer analysis method and device based on real-time fluorescent quantitative PCR. The method comprises the following steps: acquiring to-be-analyzed data; determining sample exclusive threshold line data according to the to-be-analyzed data; calculating a corrected Ct value based on double inflection point dynamics according to the exclusive threshold line data of the sample so as to obtain a final corrected Ct value; and generating a detection result according to the final corrected Ct value. Through optimization processing of the curve fitting algorithm, the linear characteristic of the fluorescence amplification curve is remarkably improved, the interference of background noise on the result is reduced, and the calculation stability of the Ct value is improved.

The invention relates to the technical field of medical risk assessment, in particular to a thyroid cancer risk assessment system and device based on multiple modes. The system comprises a data preprocessing module used for unifying formats and scales of radiomics images, transcriptomics data and clinical medicine texts; the multi-modal feature extraction module is used for extracting image data features by adopting 3D ResNet-34 as a bottom feature extractor and combining a deformable convolution technology; performing feature selection on the exosome miRNA data through a machine learning model, and performing importance sorting on features through an SHAP method; performing feature extraction on the clinical medicine text data through a multi-granularity semantic fusion network architecture; the cross-modal dynamic fusion module is used for aligning and fusing features; and the decision and interpretability module is used for generating a diagnosis result and providing interpretability analysis. According to the technical scheme, the accuracy and efficiency of thyroid cancer risk assessment can be improved.

Theranostic targeted ultrasonic blasting nano-bubbles, a preparation method therefor, and use thereof, wherein the nano-bubbles are the targeted drug-gene nano-bubbles miRNA / FTY720 / PFP@PEI-T7 NBs. The nano-bubbles can be used for preparing a thyroid ultrasound diagnostic agent or a drug for treating thyroid cancer.

Therapeutic compositions comprising chitosan-derived compositions are useful agents when administered in connection with methods for treating neoplasms, such as for instance, malignant lung, thyroid and kidney neoplasms, and other types of malignant neoplasms, and other medical disorders.

The invention relates to the field of disease risk prediction models, and discloses a thyroid cancer metastasis risk prediction model and a construction method and application thereof. The construction method of the model comprises the following steps: S1, collecting and preprocessing a sample; s2, gene expression quantity detection; s3, data set division and standardization processing; s4, constructing a deep learning model; s5, performing model evaluation; and the biomarker group for detecting the gene expression quantity in the S2 is composed of RPS4Y1, PKHD1L1, CRABP1, KRT18P8, AGPAT4, CPQ, SLC26A7 and RBP4. The prediction model can be used as a clinical auxiliary diagnosis tool and is used for guiding operation range selection, postoperative follow-up visit strategy making and early intervention of high-risk patients, and the precise diagnosis and treatment level of thyroid cancer is improved.

The invention relates to the technical field of tumor molecular imaging, nuclear medicine diagnosis and targeted therapy, and discloses a Trop2-targeted polypeptide, a Trop2-targeted molecular probe and application of the Trop2-targeted polypeptide and the Trop2-targeted molecular probe. The polypeptide can be coupled with different imaging elements to construct molecular probes or radiopharmaceuticals for tumor targeted imaging, so that noninvasive visual detection on the Trop2 expression level in tumor tissues is realized. The probe can specifically recognize Trop2 positive solid tumors, and a new technical means is provided for noninvasive diagnosis and dynamic monitoring of various Trop2 high-expression tumors such as pancreatic cancer, lung cancer, breast cancer and thyroid cancer. The probe disclosed by the invention has the advantages of simple preparation process, low cost, high specificity and stability, short imaging period, low radiation dosage, easiness in clinical transformation and the like, and has a wide application prospect in precise diagnosis and individualized treatment of tumors.

The invention relates to the technical field of intelligent rehabilitation monitoring, in particular to a real-time sticking and pricking effect monitoring system for thyroid cancer postoperative neck and shoulder function rehabilitation, which comprises a vector sequence generation module, a convergence section construction module, a direction difference calculation module, a stable section screening module and an effect monitoring module. According to the method, continuous image frames are collected, a grid observation node shadow direction vector sequence is extracted, the shadow flow trend caused by skin surface microscopic deformation is captured, and the relative deviation between the static texture main direction and the dynamic shadow vector angle is used for representing the real-time coupling degree of the sticking structure and the skin texture. Stable continuous time slices are screened through differential variation amplitude to eliminate invalid vibration interference, numerical variance is counted and calculated based on direction difference sequence dispersion degree, dynamic stability depth quantitative evaluation of a target area is achieved, and an accurate quantitative index reflecting muscle skin movement coordination is provided. The defect that the micromechanics interaction state is difficult to perceive through macroscopic contour monitoring is overcome.

The invention discloses a thyroid cancer and lymph node accurate positioning system based on three-dimensional imaging, which relates to the technical field of medical image modeling, and comprises the following steps: acquiring two-dimensional images of a cross section and a coronal plane, preprocessing the acquired two-dimensional images, extracting image features of the preprocessed two-dimensional images, and constructing a three-dimensional model based on the image features. Evaluating and adjusting the constructed three-dimensional model, displaying the adjusted three-dimensional model by using a visual tool and providing an interaction tool, generating an electronic diagnosis report based on a three-dimensional model positioning result, storing the generated electronic diagnosis report to a hospital internal database, and performing encryption measures on the access authority of the hospital internal database. According to the thyroid gland and lymph gland positioning method, feature processing is performed based on the preprocessed image, the three-dimensional model is constructed based on the feature processing result, and the adjusted three-dimensional model is displayed by using the visual tool, so that the accuracy of thyroid gland and lymph gland positioning is improved, and the complexity of an operation and the risk of lymph gland omission are reduced.

The present disclosure is concerned with compounds and compositions for use in the prevention and treatment of cancer associated with FBOX21 mediated p85a ubiquitination such as, for example, cancer (e.g., sarcoma, a carcinoma, a hematological cancer, a solid tumor, breast cancer, cervical cancer, gastrointestinal cancer, colorectal cancer, brain cancer, skin cancer, prostate cancer, ovarian cancer, thyroid cancer, testicular cancer, pancreatic cancer, liver cancer, endometrial cancer, melanoma, a glioma, leukemia, lymphoma, chronic myeloproliferative disorder, myelodysplastic syndrome, myeloproliferative neoplasm, non-small cell lung carcinoma, renal cancer, lung cancer, colon cancer, cervical cancer, and plasma cell neoplasm (myeloma)). This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present invention.

This invention discloses a method for constructing a gene methylation diagnostic model for differentiated thyroid cancer (PTC). The method includes the following steps: S1, obtaining a test sample; S2, extracting and storing DNA from the test sample; S3, performing methylation analysis; S4, establishing a diagnostic model based on DNA methylation, where the model shows that patients with cg03596178, cg06033721, cg06688989, cg07209244, cg07485775, cg14484681, cg19979108, and cg20943461 are more likely to experience disease progression and are considered risk factors; S5, cross-validating and evaluating the performance to obtain the gene methylation diagnostic model. This model, by detecting and statistically analyzing specific methylation sites, can differentiate patients with recurrent or metastatic characteristics in differentiated thyroid cancer. The relevant model can assist in the clinical diagnosis and follow-up of thyroid patients.

This disclosure provides compounds of formula (I) or pharmaceutically acceptable salts thereof, methods for preparing the same, and their use in the treatment and / or diagnosis of cancers such as neuroblastoma, prostate cancer, pancreatic cancer, leukemia, osteosarcoma, hepatoblastoma, lung cancer, colon cancer, breast cancer, skin cancer, thyroid cancer, and / or rhabdoid cancer. JPEG2026522940000099.jpg50170

The invention provides a methylation marker combination for identifying and diagnosing benign and malignant thyroid nodules or diagnosing thyroid cancer. The methylation marker combination comprises methylation TSHR, NIS and TPO genes or fragments thereof. In addition, the invention further provides a thyroid cancer diagnosis product and device based on the methylation marker combination and application of the thyroid cancer diagnosis product and device in thyroid nodule benign and malignant identification and thyroid cancer diagnosis. Whether a thyroid tissue sample or a blood sample is taken as a detection object, the methylation marker combination can realize efficient and sensitive diagnosis of thyroid cancer, and especially has outstanding performance in early thyroid cancer diagnosis, so that the methylation marker combination has a good application prospect. And the kit has important clinical application value and practical significance for early screening and diagnosis of thyroid cancer.

The invention relates to the technical field of fusion gene detection, and discloses a high-throughput detection platform of a thyroid cancer specific fusion gene CCDC6. According to the detection platform disclosed by the invention, high-throughput and high-sensitivity detection on the thyroid cancer CCDC6 fusion gene is realized through a technical scheme of combining sample enrichment and deep learning recognition. Through combination of the sample enrichment module and the deep learning recognition module, the sample enrichment module promotes high-sensitivity recognition of the deep learning recognition module, an end-to-end integrated solution is provided, a large number of samples can be processed in one-time operation, the result can be automatically interpreted, and the detection efficiency and accuracy of the CCDC6 fusion gene are remarkably improved.

The application discloses a thyroid cancer gene detection report intelligent risk assessment method, and relates to the technical field of biomedical information processing, and comprises the following steps: risk conclusion extraction is carried out on obtained multiple thyroid cancer gene detection reports, and the risk conclusion in each detection report is arranged in order of detection time, the time interval between adjacent detection reports is marked, and continuous risk change records are formed. Through time sequence processing and trend reversal identification, the application realizes dynamic analysis of risk assessment, can capture reversal signals in the early stage of risk increase, and improves the timeliness and reliability of risk identification. By setting a reference point and a risk control entrance, combining time interval insertion and detection frequency improvement, the application realizes adaptive correction and continuous updating of risk results, and enhances the real-time performance and safety of risk assessment.

A multi-modal pan-cancer early prediction method is disclosed, comprising: collecting cfDNA samples of i cancer populations and healthy populations respectively and extracting methylation data; merging CpG sites based on the methylation data to obtain multiple methylation intervals, screening multiple candidate marker intervals from the multiple methylation intervals, and further screening the multiple candidate marker intervals; training a first prediction model using the multiple candidate marker intervals, training a second prediction model based on the fragmentation characteristics of the chromosomes extracted from the reference genome, and training a third prediction model by extracting the methylation entropy characteristics of the chromosomes; training a multi-modal pan-cancer early prediction model through the cancer population prediction values of the first prediction model, the second prediction model and the third prediction model, which can provide precise joint early screening for lung cancer, intestinal cancer, gastric cancer, liver cancer, esophageal cancer, thyroid cancer and ovarian cancer.

This invention discloses a traditional Chinese medicine composition, preparation, and its application in the preparation of a drug for treating postoperative cancer-related fatigue in thyroid cancer patients. The traditional Chinese medicine composition comprises the following components in parts by weight: 30-50 parts raw Astragalus membranaceus, 5-20 parts stir-fried Atractylodes macrocephala, 5-20 parts Curculigo orchioides, 5-20 parts Epimedium brevicornu, 5-20 parts Prunella vulgaris, 5-20 parts Dendrobium nobile, and 5-20 parts Lycium barbarum. This invention combines raw Astragalus membranaceus, stir-fried Atractylodes macrocephala, Curculigo orchioides, Epimedium brevicornu, Prunella vulgaris, Dendrobium nobile, and Lycium barbarum. Through the rational combination of these raw materials, it can effectively improve immune function, relieve physical and mental fatigue, and improve the quality of life of postoperative thyroid cancer patients.

The invention relates to the technical field of medical image and artificial intelligence technology crossing, in particular to an intelligent auxiliary diagnosis method and system for a frozen section in a thyroid cancer operation. According to the technical scheme, the method comprises the following steps that a thyroid tissue intraoperative frozen section to be diagnosed is prepared, and the frozen section does not need to be dyed or subjected to section sealing treatment; and scanning the frozen section by using a terahertz near-field imaging system to obtain terahertz near-field image data of the frozen section. According to the method, the terahertz near-field imaging technology is adopted, the situation that cell nucleus morphology is difficult to observe due to ice crystal artifacts in a traditional frozen section is avoided, cancer cells are automatically recognized in combination with an AI model trained based on large-scale labeling data, and the objectivity and consistency of diagnosis are remarkably improved; meanwhile, the steps of dyeing and mounting are omitted, and rapid imaging and analysis are realized, so that the intraoperative diagnosis time is greatly shortened, and a generated visual contour report also provides visual decision support for pathologists.

The application belongs to the field of biological medicine, and relates to a composition, a kit and application for thyroid cancer detection. The primer composition can be used for simultaneously detecting mutation or fusion of five gene sites of two genes, BRAF gene and RET-PTC gene, and can be used for detecting thyroid cancer and has high sensitivity and specificity. Meanwhile, the fluorescence PCR technology is adopted to improve detection efficiency, shorten detection time and realize precise diagnosis of thyroid cancer.

The application discloses a series of derivatives based on natural product gelsemium methyl, pharmaceutically acceptable salts and preparation methods thereof. Bioactivity tests show that the compounds have the effect of inhibiting the proliferation of various tumor cells. The compounds can be used for the treatment of various cancers (including but not limited to gastric cancer, liver cancer, lung cancer, esophageal cancer, cervical cancer, breast cancer, colon cancer, rectal cancer, nasopharyngeal cancer, ovarian cancer, kidney cancer, bladder cancer, thyroid cancer and skin cancer) as active pharmaceutical ingredients.

The present invention discloses a method for treating thyroid cancer using a radiolabeled cleavage-type Evans Blue degenerated fibroblast-activating protein inhibitor, said drug having excellent safety and tolerance in patients with thyroid cancer and having a very excellent therapeutic prospect in the treatment of thyroid cancer.

The application discloses a kind of information management method and related equipment for thyroid cancer postoperative iodine 131 treatment patient.It comprises: based on the treatment management data of patient, scheduling model is constructed with patient waiting time, medical interaction cost and isolation bed vacancy time as optimization target, and bed capacity constraint, clinical urgency constraint, radiation protection constraint and medical availability constraint are established;Based on the scheduling model and the constraint condition, the joint optimization of patient reservation admission batch, isolation bed allocation and medical communication task is carried out, and the treatment scheduling result is generated;In the case where patient temporary adjustment, bed state change or iodine 131 treatment preparation abnormality is monitored, the treatment scheduling result is dynamically rearranged, so as to execute patient reminder, treatment connection and follow-up management according to the treatment scheduling result after rearrangement.It can solve the problems of low efficiency of reservation and resource coordination, fragmented medical records and lack of dynamic tracking mechanism in traditional information management mode.

Antibody drug conjugate (ADC) comprising a drug moiety conjugated to antibody or antigen binding fragments thereof that bind to TROP2 disclosed herein, as well as methods of use thereof. Methods of use include, without limitation, cancer therapies and diagnostics. The ADC of the disclosure can bind to certain cancer cell surfaces. Exemplary targets of the ADC disclosed herein can include carcinomas, such as lung cancer, breast cancer, head-and-neck cancer, esophagus cancer, stomach cancer, bladder cancer, pancreatic cancer, colorectal cancer, cervix cancer, endometrial cancer, ovarian cancer, laryngeal cancer, prostate cancer, thyroid cancer and oral cancer.

The invention relates to the technical field of medical data processing, in particular to a thyroid cancer postoperative bleeding risk prediction system. The system comprises a prediction probability obtaining module used for obtaining feature data of a patient, forming a training set and a verification set, and obtaining the bleeding prediction probability of each sample in the verification set; the clustering analysis module is used for clustering the bleeding prediction probability of each sample in the verification set to obtain clusters, and analyzing each cluster to obtain a standard deviation distance; the credible analysis module is used for acquiring a predicted deviation index; obtaining a clinical credibility score of the prediction model according to the standard deviation distance, the prediction deviation index and an AUC value of the prediction model; the prediction model adjusting module is used for determining whether the prediction model needs to be optimized or not and obtaining a final prediction model; and predicting whether the patient bleeding after operation by using the final prediction model. According to the method, the postoperative bleeding risk of the patient can be accurately predicted.

The application discloses a chaga acidic polysaccharide IOP-2 with anti-thyroid cancer activity and application thereof, and belongs to the field of biological medicines. The application adopts a method for extracting chaga polysaccharide by boiling water and precipitating chaga polysaccharide by ethanol, and combines DEAE cellulose column purification technology, and successfully realizes separation of chaga polysaccharide by using the principle that macromolecular polysaccharide is insoluble in organic solvents, and obtains chaga acidic polysaccharide IOP-2 with anti-thyroid cancer activity. The monosaccharide composition of the chaga acidic polysaccharide IOP-2 includes fucose 0.71%, rhamnose 3.33%, arabinose 2.18%, galactose 2.92%, glucose 80.59%, xylan 3.46% and mannose 6.81% in terms of molar percentage. The significant effect of the chaga acidic polysaccharide IOP-2 on anti-thyroid cancer is verified through in-vivo and in-vitro experiments, and a new treatment method is provided for clinical treatment of thyroid cancer.

The present disclosure relates to RNAi agents useful in methods of treating KRAS-related diseases such as a proliferative disease, including without limitation a solid or liquid cancer, adenocarcinoma, colorectal cancer, advanced and / or metastatic colorectal cancer, colon cancer, lung, non-small cell lung cancer and lung adenocarcinoma, acute myelogenous lung, bladder, brain, breast, cervical, endometrial, gastric, head and neck, kidney, leukemia, myelodysplastic syndrome, myeloid leukemia, liver, melanoma, ovarian, pancreatic, prostate, testicular, thyroid cancers, and cardio-facio-cutaneous (CFC) syndrome and Noonan syndrome, and similar and related diseases, using a therapeutically effective amount of a RNAi agent to KRAS.

The invention discloses inonotus obliquus acidic polysaccharide IOP-2 with thyroid cancer resisting activity and application of the inonotus obliquus acidic polysaccharide IOP-2, and belongs to the field of biological medicine. According to the invention, a method for extracting inonotus obliquus polysaccharide by boiling water and precipitating the inonotus obliquus polysaccharide by ethanol is adopted, a DEAE cellulose column purification technology is combined, and the principle that macromolecular polysaccharide is insoluble in an organic solvent is utilized, so that the separation of the inonotus obliquus polysaccharide is successfully realized, and the inonotus obliquus acidic polysaccharide IOP-2 with thyroid cancer resisting activity is obtained; the monosaccharide of the inonotus obliquus acidic polysaccharide IOP-2 is prepared from the following components in percentage by mole: 0.71 percent of fucose, 3.33 percent of rhamnose, 2.18 percent of arabinose, 2.92 percent of galactose, 80.59 percent of glucose, 3.46 percent of xylan and 6.81 percent of mannose. In-vivo and in-vitro experiments prove that the traditional Chinese medicine composition has a remarkable thyroid cancer resisting effect, and a novel treatment method is provided for clinical treatment of thyroid cancer.

According to the thyroid cancer typing system based on the double-flow network, an image acquisition and preprocessing module acquires thyroid nodule ultrasonic image data and preprocesses the thyroid nodule ultrasonic image data to obtain standard image data; the classification module obtains benign and malignant classification results through the first-stage network; the typing module obtains a thyroid cancer typing result through the second-stage network; the decision module judges the nodule state based on the benign and malignant classification result, and if the nodule state is judged to be benign, a benign result is output; and if the judgment result is malignant, inputting into a typing module. The method has the progressive logic conforming to clinical diagnosis of judging good and bad first and then determining and typing, adopts a staged progressive network architecture, and preferentially excludes a large number of benign cases through the first-stage network to reduce the distinguishing burden and complexity of the second-stage network, so that the network in each stage can focus on learning the specific task characteristics, and the network efficiency is improved. And moreover, multi-path parallel extraction of nodule multi-dimensional features is adopted for cross fusion for pathological subtype typing, so that the accuracy is high.