345 results about "AIDS diagnosis" patented technology

The invention relates to the field of disease prediction, in particular to an epilepsy prediction system based on synchronously acquired electroencephalogram-gastric electrical signals, comprising: a data acquisition module for acquiring data including electroencephalogram data and gastrointestinal electrical data; the first analysis module is used for obtaining an average electrode inconsistency index of the first channel and the second channel based on a first model according to the time sequence data; and the prediction module is used for comparing the average electrode inconsistency index of the subject with a preset evaluation threshold value so as to predict an epileptic. The system provided by the invention can more accurately and efficiently distinguish epilepsy patients from healthy people, and can be used as an auxiliary diagnosis tool to be applied to primary screening of epilepsy of relatively large people (such as communities and physical examination centers).

The invention discloses development, preparation and application of a carbapenemase immunochromatography kit, and belongs to the technical field of biological medicines. According to comparison of amino acid sequences of five common carbapenemase variants of KPC, IMP, NDM, VIM and OXA48 types, the immunogen is prepared from conserved epitope sequences obtained respectively. A mouse is immunized, and a specific antibody pair which is strong in affinity and can be combined with multiple variants is obtained through multi-platform screening. On the basis, the carbapenemase quintuplet detection kit is developed by utilizing an immunochromatography method, has the advantages of high sensitivity, good specificity, capability of covering various drug-resistant variants, capability of detecting multiple targets at one time and rapidness and convenience in detection, and provides important help for clinical auxiliary diagnosis and medication guidance.

The invention discloses preparation of an antibody capable of detecting multi-subtype KPC and application of a kit of the antibody, and belongs to the field of biological medicine. According to the kit for detecting the common subtypes of KPC and the application of the kit, the mouse antibodies are prepared through immunization of conserved antigen epitopes of all the subtypes of KPC, in-vitro screening and pairing are carried out in multiple modes, then an antibody pair which is good in specificity and high in affinity and can be combined with multiple subtypes is obtained, the titer of the two antibodies can reach one million or above, and the kit is high in specificity, good in affinity and capable of being used for detecting the common subtypes of KPC. Amino acid sequences of a heavy chain variable region and a light chain variable region are obtained through sequencing, and rapid and stable expression can be realized after recombination. The product for detecting the carbapenem KPC is developed on the basis of an immunochromatography platform, and the kit has the advantages of high sensitivity, good specificity, good stability, capability of covering most epidemic KPC subtypes and rapidness and convenience in detection, and provides important help for clinical auxiliary diagnosis and medication guidance.

The invention discloses an autophagy biomarker related to depression, a risk assessment model and application of the autophagy biomarker. A group of autophagy related biomarkers for auxiliary diagnosis of depression are screened out through multi-dimensional screening of large sample data and a machine learning algorithm, the autophagy related biomarkers comprise the following genes: GABARAPL2, RB1CC1, FOS and ULK1, and differential expression of the autophagy related biomarkers is proved in chronic stress induced depression-like mouse cortical brain tissues. The invention also provides a risk assessment model for auxiliary diagnosis of depression, a logistic regression model is constructed by taking the biomarker as a feature, a score formula and a risk boundary value of depression risk assessment are determined, and multi-aspect assessment is carried out on the prediction performance of the model. The prediction model has good prediction accuracy and calibration degree, can efficiently and conveniently realize early diagnosis of depression, and improves the accuracy of depression treatment.

The invention belongs to the field of biomedicine, and particularly relates to application of ABCG1 in diagnosis or auxiliary diagnosis of HIV (human immunodeficiency virus) combined hyperlipidemia. Through detection, the expression of the ABCG1 in the blood of a patient with HIV combined with hyperlipidemia is obviously reduced, the ABCG1 is verified to have the characteristics of high sensitivity and high specificity, whether hyperlipidemia exists in an HIV infected group or not can be diagnosed or diagnosed in an auxiliary manner by detecting the expression of the ABCG1, guidance is provided for early intervention of hyperlipidemia in the HIV infected group, and the method is suitable for clinical application. Wide clinical application prospects are realized.

The invention relates to the technical field of medical clinical auxiliary diagnosis, in particular to an orthopedic postoperative complication early detection and early warning system based on data analysis, which comprises a multi-modal sign synchronous acquisition module, a sign dynamic difference quantification module, a complication feature association module, a grading early warning decision module and a dissection calibration visualization module. Wherein the multi-modal sign synchronous acquisition module is used for acquiring postoperative data of a patient; calculating a difference quantization parameter; the complication characteristic association module is used for identifying associated risk characteristics of the osteofascia ventricular syndrome, the deep venous thrombosis and the fat embolism; and the grading early warning decision module is used for generating a three-level early warning instruction based on the associated risk characteristics. According to the system and the method, through a multi-modal sign synchronous acquisition, difference quantification and grading early warning linkage mechanism, accurate recognition, risk grade division and visual intervention guidance of postoperative complications are realized, and the continuity of postoperative monitoring and the timeliness of early warning are improved.

The invention is applicable to the technical field of biological detection, provides a fluorescence immunochromatography detection method based on monatomic nano-enzyme enhancement, and particularly relates to two application forms: in the first form, a detection signal enhanced fluorescence immunochromatography detection card and a sample diluent containing a monatomic nano-enzyme are involved; in the second form, the invention relates to a fluorescence immunochromatography detection card with enhanced detection signals, and a sample pad of the detection card is obtained by soaking a sample pad treatment solution containing a monatomic nano-enzyme solution. The two application forms both relate to a monatomic nano-enzyme solution, and the solution is composed of monatomic nano-enzyme, bio-enzyme composite microspheres, a protective agent, a surfactant, a thickening agent and a preservative. The monatomic nano enzyme is composed of an atomic-scale dispersed metal active center and a carrier material. When the method is used for detecting myocardial and inflammatory markers, the limit of quantitation can reach the pg / mL level, the detection linear range can span three orders of magnitude, and the clinical examination use requirements can be met. The kit can be applied to rapid quantitative detection of myocardial and inflammatory markers, has the advantages of high sensitivity, rapidness, convenience and high efficiency, and provides an auxiliary diagnosis basis for early screening of myocardial infarction, heart failure and infection related diseases.

The invention belongs to the technical field of biological medicine, and particularly relates to a kit for breast cancer diagnosis and application thereof. The kit comprises an elisa plate coated with a captured antibody and an HRP labeled antibody working solution, the capture antibody is a monoclonal antibody T2X-1 of an anti-PSTPIP1 protein; the HRP labeled antibody is a monoclonal antibody Z4Y-2 of an anti-PSTPIP1 protein, and the HRP labeled antibody is a monoclonal antibody Z4Y-2 of an The heavy chain amino acid sequence of the monoclonal antibody T2X-1 is as shown in SEQ ID NO.1, and the light chain amino acid sequence of the monoclonal antibody T2X-1 is as shown in SEQ ID NO.2; the heavy chain amino acid sequence of the monoclonal antibody Z4Y-2 is as shown in SEQ ID NO.3, and the light chain amino acid sequence of the monoclonal antibody Z4Y-2 is as shown in SEQ ID NO.4. The kit for breast cancer diagnosis provided by the invention can be used as an auxiliary diagnosis means for breast cancer with high expression of PSTPIP1 protein, and has high diagnostic value.

The invention discloses a recombinant protein and a detection reagent for detecting encephalitis of an anti-GABABR antibody, and belongs to the technical field of neuroimmunology diagnos.A GABABR1 partial sequence, a GABABR2 partial sequence and a transmembrane sequence (and a fluorescent label) are adopted to construct a cell strain for stably and highly expressing the recombinant protein by transfecting CHO cells or HEK293 cells, and the recombinant protein and the detection reagent are used for detecting the encephalitis of the anti-GABABR antibody. The sensitivity and the specificity of the kit in anti-GABABR antibody encephalitis detection can be remarkably improved, the aim of detecting the antibody by using a fixed CBA method or a living cell CBA method can be achieved, and the kit is suitable for auxiliary diagnosis of autoimmune encephalitis of cerebrospinal fluid / serum.

The invention provides a group of metabolic markers, a kit and application of the metabolic markers in auxiliary diagnosis of schizophrenia. The metabolic markers comprise arachidonic acid, palmitamide and lysophosphatidylcholine (LPC) (17: 0 / 0: 0). By utilizing the metabolic marker, auxiliary diagnosis of schizophrenia can be rapidly and accurately completed in the early stage of disease attack.

The invention discloses a mental disease medical auxiliary diagnosis method based on a bimodal knowledge graph and a related device, and relates to the technical field of mental disease diagnos.The method comprises the steps that a static medical diagnosis knowledge graph is constructed; generating a scenarized problem library based on the static medical diagnosis knowledge graph; dynamically updating a personal dynamic knowledge graph based on interaction between the scenarized question library and a user; and finally, optimizing the static medical diagnosis knowledge graph based on the personal dynamic knowledge graph. According to the invention, through cooperation of the static and dynamic knowledge maps, objectivity, dynamics and accuracy of mental disease diagnosis are improved, and closed-loop management of medical auxiliary diagnosis is realized.

The invention relates to the technical field of liver cancer analysis, in particular to a liver cancer analysis method, system and equipment based on multi-modal deep learning and a medium. The method comprises the following steps: acquiring pathological data, transcriptome data, methylation data and clinical data of a target patient, and respectively preprocessing to obtain target pathological data, target transcriptome data, target methylation data and target clinical data; respectively carrying out feature extraction to obtain pathological features, transcriptome features, methylation features and clinical features; performing feature fusion on the pathological features, the transcriptome features, the methylation features and the clinical features to obtain liver cancer analysis features; extracting lipid metabolism related marker characteristics of the target patient, and performing liver cancer comprehensive analysis on the target patient according to the lipid metabolism related marker characteristics and the liver cancer analysis characteristics. According to the application, the tumor characteristics of the target patient can be comprehensively reflected, the accuracy of auxiliary diagnosis is improved, and accurate prognosis prediction is provided for the target patient.

The invention discloses a biomarker for auxiliary diagnosis of lung adenocarcinoma bone metastasis. The invention specifically provides application of a biomarker or a detection reagent thereof in preparation of a product for auxiliary diagnosis or early screening of lung adenocarcinoma bone metastasis. The biomarker is AA and / or ANGPTL4. According to the invention, AA and / or ANGPTL4 are / is applied to diagnosis of lung adenocarcinoma bone metastasis for the first time, and a simple, non-invasive and long-term available detection method is provided through serum detection; compared with the prior art, earlier bone metastasis diagnosis can be achieved, health risks caused by radiation are avoided, and high clinical application value is achieved; in a word, the invention provides a new biomarker combination for early diagnosis of lung adenocarcinoma bone metastasis, is expected to provide more accurate guidance for clinical treatment of patients, and has important significance for long-term monitoring of tumor metastasis.

The invention relates to the technical field of biology, in particular to application of synaptic binding protein 11 serving as a marker to preparation of products for diagnosis, auxiliary diagnosis, screening or auxiliary screening of schizophrenia and application of the synaptic binding protein 11 and / or a dopamine D2 receptor serving as a core target to treatment of schizophrenia. The application of the synaptic binding protein 11 or the transcriptional product mRNA or the mRNA fragment of the synaptic binding protein 11 as the marker in any one of the following items: 1) application in preparation of products for diagnosis or auxiliary diagnosis of schizophrenia of human or non-human mammals; 2) application in preparation of products for screening or auxiliary screening of schizophrenia of human or non-human mammals; 3) application in diagnosis or auxiliary diagnosis of schizophrenia of human or non-human mammals to be detected; and 4) application in screening or auxiliary screening of schizophrenia of human or non-human mammals to be detected. Meanwhile, the invention also provides application of treating three symptoms of schizophrenia through a brain region specific targeting dopamine D2 receptor. Researches find that synaptic binding protein 11 or a transcription product mRNA or mRNA fragment thereof can be used as a brand new functional schizophrenia diagnosis marker, and a chemical molecule or gene therapy drug targeting synaptic binding protein 11 or a dopamine D2 receptor can effectively improve three symptoms of schizophrenia.

The invention provides an intelligent diagnosis and treatment method and system for teenager depression based on large model collaboration, and the method comprises the steps: constructing a remote sensing human living microenvironment and growth soft environment data set, carrying out the preprocessing and feature extraction of the data set, carrying out the space-time matching and characterization of the environment and the brain-behavior clinical data of a subject individual, and carrying out the diagnosis and treatment of the teenager depression. Individual intervention queue data and feature representation matched with the environment are collected; establishing a knowledge graph based on a large model based on the acquired multi-dimensional data; and performing intelligent diagnosis and intervention of environment-brain-behavior enhancement based on the established knowledge graph. Based on a knowledge organization system of environment-brain-behavior auxiliary diagnosis, pathogenesis evaluation and individualized intervention, an environment-brain-behavior multi-dimensional knowledge graph oriented to adolescent depression diagnosis is constructed, and based on a large-model collaborative reasoning mechanism enhanced by environment-brain-behavior multi-dimensional knowledge, the adolescent depression diagnosis is more accurate. An intelligent and precise method system is provided for diagnosis and treatment of juvenile depression, and the diagnosis and treatment level is greatly improved.

The invention belongs to the field of biological medicine, and discloses a blood marker for identifying epilepsy convulsion and application thereof. The inventor finds that the LRG1 is obviously increased during epileptic convulsion, which indicates that the increase of the blood LRG1 is a blood marker during the acute attack stage of epileptic convulsion. The invention proposes and verifies that the LRG1 is the peripheral blood marker in the acute attack stage of epilepsy convulsion for the first time, and can be used as a clinical auxiliary diagnosis and treatment target.

The invention discloses an active tuberculosis diagnostic marker, a kit and application thereof. In particular to application of a reagent for detecting a diagnostic marker in preparation of a kit for diagnosing active tuberculosis, the diagnostic marker is a biomarker TRIM22 in a blood sample, and the sequence of the TRIM22 is as shown in SEQ ID NO: 1. According to the invention, TRIM22 in a blood sample is used as a biomarker for detecting active tuberculosis for the first time. Results of ROC curve analysis show that the expression level of TRIM22 in whole blood has good sensitivity and specificity for active tuberculosis diagnosis. Therefore, the invention overcomes the defects of low detection rate, long time consumption and the like of the existing active tuberculosis diagnosis, has the characteristics of good specificity and high sensitivity, and has good clinical application value for the auxiliary diagnosis of the active tuberculosis.

The invention relates to the technical field of tumor markers, in particular to a pancreatic cancer early screening marker combination based on blood protein and application of the pancreatic cancer early screening marker combination. Through proteomics analysis and bioinformatics screening, 12 kinds of proteins such as NME3, HPGDS, CEACAM5, TNFSF12, SCG3, VTCN1, GFRA1, KRT19, TMPRSS12, NELL2, KAZALD and MMP12 are determined to serve as the potential early screening markers of the pancreatic cancer. Researches show that the combination of the proteins can effectively distinguish pancreatic cancer patients from non-pancreatic cancer patients, and has good sensitivity and specificity. A screening model constructed based on the protein combination can be applied to auxiliary diagnosis, risk assessment and population screening of pancreatic cancer, and has important clinical transformation value.

The invention provides a plurality of microbial markers for cervical cancer and an application of the microbial markers. The microbial markers comprise 11 bacteria, namely, Porphyromonas aeruginosa, Lactobacillus crispatus, Klebsiella pneumoniae, Gemerella haemolysms and the like, and the microbial markers comprise 11 bacteria, namely, the Porphyromonas aeruginosa, the Lactobacillus crispatus, the Klebsiella pneumoniae, the Gemerella haemolysms and the like. According to the method, the threshold value of the output risk value is obtained according to the trained random forest model, and then the probability value that the cervical lesion sample is the high-risk lesion can be obtained only by obtaining the relative abundance of the screened 11 genital tract microbial markers and inputting the relative abundance into the established random forest model. The machine learning model is constructed based on 16S sequencing, the high risk of cervical cancer can be recognized in time, the method is used for auxiliary diagnosis of cervical cancer patients, early discovery, early prevention and early treatment of cervical cancer are facilitated, and the accessibility of cervical cancer screening is improved.

The invention relates to the field of middle-axis type spinal arthritis diagnosis, in particular to a middle-axis type spinal arthritis auxiliary diagnosis and analysis system based on PSO-TabNet, and the system comprises a data collection unit which is used for collecting clinical feature data and iconography feature data; the data preprocessing unit is used for preprocessing the feature data; the axSpA prediction model construction unit is used for optimizing a TabNet model hyper-parameter by using a particle swarm algorithm to obtain a PSO-TabNet model; and the prediction analysis unit is used for performing axSpA classification prediction on the clinical data based on the PSO-TabNet model to obtain auxiliary diagnosis suggestions. According to the invention, the PSO algorithm is adopted to optimize the hyper-parameters in the TabNet model, the PSO algorithm can automatically adjust the hyper-parameters, manual intervention is not needed, the complexity of hyper-parameter adjustment is reduced, the stability and effect of the model are improved, and doctors can be more reliably assisted in diagnosing diseases.

The invention relates to the technical field of medical detection, in particular to application of a TTR tetramer in preparation of a product for diagnosing ejection fraction retention type heart failure. Experiments prove that in heart failure patients, TTR tetramers in HFpEF patients are obviously higher than those in non-HFpEF patients, and it is prompted that the TTR tetramers are related to HFpEF. According to the present invention, the diagnosis model and the kit using the TTR tetramer as the biomarker have good sensitivity and good specificity, can achieve the diagnosis or the auxiliary diagnosis, the treatment guidance and the prognosis of the HFpEF, and can improve the identification of different heart failure types such as the HFpEF and the non-HFpEF.

The invention discloses a biomarker for diagnosing systemic lupus erythematosus and lupus nephritis and application of the biomarker, and relates to the technical field of biological medicines. The biomarker is an ISG15hiCD16 < + > mononuclear cell. According to the application disclosed by the invention, the ISG15hiCD16 + mononuclear cell subpopulation is found to be obviously increased in an SLE (systemic lupus erythematosus) patient. The invention also finds that the expression level of the ISG15hiCD16 + mononuclear cell subpopulation is positively correlated with the disease activity of the SLE patient, and the expression level of the ISG15hiCD16 + mononuclear cell subpopulation of the SLE patient with the kidney enduring expression is obviously higher than that of the SLE patient without the kidney enduring expression. The working characteristic curve analysis of a subject shows that the ISG15hiCD16 + mononuclear cell subset has better sensitivity and specificity for diagnosing the SLE and the LN, and has important significance for clinical auxiliary diagnosis of the SLE and the LN and illness state evaluation.

The invention discloses application of astrocyte-derived extracellular vesicles carrying Tau in auxiliary diagnosis of progressive suprakaryotic paralysis, and belongs to the technical field of biomedicine. The specific Tau protein antibody and the anti-glutamic acid transporter 1 antibody are labeled by fluorescence, astrocyte-derived extracellular vesicles carrying Tau in the plasma are accurately detected, PSP patients, PD patients and healthy people can be accurately distinguished by analyzing the concentration of astrocyte-derived EVs carrying Tau in the plasma, and the kit has the advantages of high sensitivity, high sensitivity, high sensitivity and the like. An efficient PSP diagnosis biomarker and a diagnosis model are provided, and a new experience method and technical support are provided for PSP diagnosis and identification.

The invention provides a method and a system for predicting early gastric cancer prognosis by a circulating marker, and relates to the technical field of auxiliary diagnosis. The method comprises the following steps: performing multi-omics detection on a blood sample based on a preset sampling time sequence to obtain a multi-dimensional time sequence characteristic data set containing three groups of heterogeneous data of circulating tumor DNA, exosomes and protein markers; calculating a change slope and a fluctuation variance of the heterogeneous data in adjacent time sequence intervals, constructing a dynamic variation feature matrix in combination with a standard attenuation weighting factor, and deeply mining spatial cross-correlation and sequence dependence features of the matrix to generate a multi-modal fusion feature fingerprint; and performing regression operation on the feature fingerprints by using an integrated learning stack model to obtain a dynamic prognosis risk score, and further retrieving a risk hierarchical mapping table to generate a prognosis evaluation result containing a survival curve. According to the method, multi-modal heterogeneous data can be effectively fused, the biological dynamic characteristics in the tumor postoperative recovery phase are captured, and the accuracy and timeliness of early gastric cancer prognosis prediction are remarkably improved.

The invention relates to application of SMAD6 in auxiliary diagnosis and prognosis evaluation of TGCT (Transforming Growth Computed Tomography). According to the invention, a novel TGCT prognosis biomarker (SMAD6) is identified through difference analysis, Cox regression and survival analysis on the basis of a TGCT sample in multiple centers. Subsequently, the expression level of SMAD6 in normal testicular tissues and TGCT is evaluated through immunohistochemical staining. Finally, the relationship between the SMAD6 and biological characteristics, mutation landscape, immune cell infiltration and immunotherapy response is also studied. The invention defines that SMAD6 is a risk factor of poor TGCT prognosis. An immunohistochemical result shows that the SMAD6 is highly expressed in the TGCT tissue. GSEA shows that SMAD6 is related to activation of tumor-related pathways and inhibition of immune-related pathways. In addition, high SMAD6 expression is associated with lower CD8 + T cell infiltration, while patients with low SMAD6 expression gain more benefits in immunotherapy. The invention fully reveals the potential of SMAD6 as a TGCT prognosis and immunotherapy reaction biomarker, and provides a new scientific basis and theoretical basis for personalized treatment of TGCT.

The invention discloses application of CREB3L1 in diagnosis and treatment of systemic sclerosis, and belongs to the technical field of biological medicine. The invention discovers that CREB3L1 has the function of regulating and controlling fibrosis of skin and lung tissues of a patient with systemic sclerosis for the first time, and plays an important role in the progress of fibrosis of systemic sclerosis. The CREB3L1 can be used as a biomarker for diagnosis and auxiliary diagnosis of systemic sclerosis, and the CREB3L1 inhibitor can be used as an effective component for controlling and / or reversing fibrosis of systemic sclerosis, and has a good clinical application prospect. A new target is provided for diagnosis and treatment of systemic sclerosis, and a solid research foundation is laid for development of drugs for resisting systemic sclerosis fibrosis.

The invention relates to the technical field of medical diagnosis, and provides a multi-modal dementia analysis auxiliary diagnosis method, system and device, a medium and equipment, and the method comprises the steps: obtaining an inquiry video of a patient, and carrying out the multi-modal feature extraction of the video, and obtaining a multi-modal feature data set; analyzing the voice feature data based on a large language model and a preset voice standard to obtain voice dimension information; analyzing the text feature data based on a large language model and a preset text standard to obtain text dimension information; analyzing the visual feature data based on a large language model and a preset visual standard to obtain visual dimension information; performing time alignment processing and feature fusion processing on the modal feature data to obtain a comprehensive multi-modal feature vector; and carrying out dementia symptom diagnosis analysis based on the large language model and a pre-constructed clinical dementia rating scale, and determining a diagnosis result based on an analysis result and the modal dimension information. The accuracy and efficiency of dementia diagnosis can be improved.

The invention discloses a KMT2A fusion gene detection primer probe group, a kit and a detection method, the primer probe group is specifically designed based on KMT2A gene fusion and 13 common partner genes MLLT3, AFF1, MLLT10, MLLT1, MLLT4, ELL, EPS15, SEPT6, MLLT11, MLLT6, SEPT9, AFF3 and CBL fusion sites, the mutual interference is small, the primer probe group can be used for targeted amplification of a fusion gene specific region in a single-tube mixed solution, the detection sensitivity is high, the detection time is short, the detection time is short, and the detection efficiency is high. According to the present invention, the rapid detection of any one fusion gene type in 67 types can be achieved, and compared with the high-throughput sequencing, the sensitivity is high, the detection rate is high, the single sample detection cost is low, the method is suitable for the clinical auxiliary diagnosis of the large batch of samples, and the guidance is provided for the diagnosis, the treatment and the prognosis of the blood disease patients.

The invention discloses a juvenile depressive disorder diagnosis marker, a depressive disorder diagnosis model and application thereof, and relates to the technical field of mental disorder diagnosis. Adiponectin is applied to auxiliary diagnosis or diagnosis of adolescent depressive disorder, the AUC value of a diagnosis model is larger than 0.7, and the adiponectin is high in diagnosis sensitivity and specificity and can serve as a diagnosis or auxiliary diagnosis marker of adolescent depressive disorder. Adiponectin and other indexes are combined for detection, the diagnosis performance of auxiliary diagnosis of juvenile depressive disorder can be improved, and the method has a good clinical application prospect.

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.