13 results about "Serum biomarkers" patented technology

The present application relates to the technical field of medical data fusion processing, and discloses a method and system for predicting adverse pregnancy outcomes of preeclampsia by fusing placental microenvironment image features and serum biomarkers, wherein the method comprises: obtaining digital whole field image of placental tissue section and serum biomarker detection data at the same period; constructing a multi-modal sample data set; extracting multi-scale structure features of placental microenvironment; constructing serum biomarker discriminant features; dynamically fusing placental image features and serum marker features; constructing a prediction model for adverse pregnancy outcomes of preeclampsia and outputting a prediction probability. Compared with the prior art which only relies on single image information or single serum biomarker for risk assessment, it is difficult to realize stable prediction of the coordinated changes of placental microenvironment abnormalities and biochemical abnormalities. Due to the multi-scale image structure analysis, the model generalization ability for predicting adverse pregnancy outcomes of preeclampsia is improved.

This invention relates to the field of medical diagnostic technology and discloses a non-invasive early DCM analysis method based on multi-radiomics and serum biomarkers. The method involves acquiring image data using multimodal medical imaging equipment and serum biomarker data using blood testing equipment; generating radiomics feature sets and serum biomarker time-series feature sets using multi-scale feature extraction algorithms and temporal analysis models, respectively; fusing these features using a dynamic weighted fusion strategy to generate a joint feature matrix; inputting this matrix into a pre-trained multi-task deep learning model to predict the probability of DCM risk; and finally, optimizing the diagnostic decision tree based on a genetic algorithm to output the early DCM diagnostic result. This method is non-invasive, accurate, and can effectively improve the accuracy of early DCM diagnosis.

This invention discloses an early ovarian cancer auxiliary diagnostic system based on multimodal fusion, belonging to the field of early ovarian cancer auxiliary diagnostic technology. It includes a data acquisition module, an image feature extraction module, a non-image feature extraction module, a multimodal fusion module, and a diagnostic output module. The data acquisition module acquires raw ultrasound images, serum biomarker test values, and clinical variable data; the image feature extraction module extracts image depth features; the non-image feature extraction module extracts non-image features; the multimodal fusion module dynamically calculates the attention weights of the two modalities and generates fused features; and the diagnostic output module outputs risk probability values. This invention overcomes the limitations of single-modal diagnosis by dynamically and adaptively fusing multimodal data such as ultrasound images, serum biomarkers, and clinical variables, significantly improving the accuracy of early ovarian cancer diagnosis, while also possessing interpretability and clinical deployment feasibility.

The invention discloses a gastrointestinal tumor patient postoperative weakness risk correlation analysis method and system fused with a co-disease map, and belongs to the field of medical care informatics, and the method comprises the following steps: obtaining clinical pathological characteristics, co-disease assessment, serum biomarkers and social and psychological assessment scale data of gastrointestinal tumor patients; obtaining statistical effect values of homocysteine and health attainment, and executing isomorphic mapping; identifying a chained intermediary conduction path and generating a coupling strength factor, and performing weighted correction on the initialized weight matrix; inputting the multi-source data as a risk source excitation signal into the atlas, executing correction calculation, and outputting a risk prediction score; a maximum weight subgraph search is performed to generate risk attribution analysis data. According to the method, the multi-dimensional heterogeneous association map is constructed to fuse the multi-source data of the patient and the medical priori knowledge, and the risk conduction is quantified through the path topology analysis and the matrix correction operation, so that the accurate prediction of the postoperative weakness risk and the interpretable attribution of the key pathogenic path can be realized.

The invention belongs to the technical field of disease prognosis and molecular biology, and relates to a flora marker for colorectal cancer liver metastasis diagnosis and liver metastasis risk assessment and application of the flora marker. The marker comprises the following three strains: bifidobacterium bifidum, bacteroides fragilis and bacteroides heparinidolyticus. The method comprises the following steps: acquiring information of microorganisms in excrement of a patient through a high-resolution metagenomics detection technology; a random forest algorithm is utilized to construct a colorectal cancer liver metastasis classification model based on the flora markers, the model can distinguish people without colorectal cancer metastasis and people with liver metastasis and accurately predict high-risk patients with colorectal cancer liver metastasis, and the effect of the model is superior to that of a clinical conventional tumor serum marker. The kit has the advantages of noninvasive detection and high accuracy, and can provide a reliable tool for liver metastasis diagnosis and individualized prognosis management of colorectal cancer patients.

This invention relates to ficolin-2, a serum biomarker for assessing carotid atherosclerotic plaques, and its applications, belonging to the field of biomedical technology. To address the urgent need for readily available and repeatable circulating biomarkers that reflect the unstable state of atherosclerotic plaques, particularly their hemorrhagic characteristics, this invention provides the application of ficolin-2 as a serum biomarker in the preparation of products for assessing the stability of atherosclerotic plaques and the prognosis of sonodynamic therapy for atherosclerosis. This invention is the first to use serum ficolin-2 protein as an efficacy monitoring indicator for SDT treatment of hemorrhagic carotid plaques, monitoring the level of complement activation-related inflammation within the plaque, enabling dynamic management of patient treatment, filling the gap in the quantification of efficacy in hemorrhagic plaque treatment, and providing a key tool for the clinical translation of emerging therapies such as sonodynamic therapy.

The application provides serum biomarkers for diagnosing and evaluating the activity of aortitis and application, and relates to the field of disease activity evaluation. The serum biomarkers are serum proteins: HP and ORM1. HP and ORM1 are determined as two new serum biomarkers through comprehensive proteomics analysis; gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis are carried out using a DAVID database; a protein-protein interaction network is constructed using Metascape. A random forest model is trained using a caret package, and a nomogram is visualized using an rms package. Serum samples are obtained, and the serum levels of HP and ORM1 are determined using a commercial ELISA kit; they are significantly related to disease activity, and are involved in inflammation / immune processes in aortitis, so the markers have the potential to serve as an auxiliary tool for monitoring the activity of aortitis.

The application relates to the technical field of medical systems, and particularly discloses a construction method of a cancer cachexia prognosis composite index CCAR based on a combination of creatinine and CAR, which comprises the following steps: S1, obtaining serum biomarker data of a cancer cachexia patient, including creatinine, C-reactive protein and albumin; S2, calculating a C-reactive protein to albumin ratio CAR=CRP / Albumin; S3, taking CAR and Cr as input features, and constructing a nonlinear composite index CCAR through a random forest machine learning model; and S4, developing a network calculator system; the CCAR index constructed by the application can comprehensively reflect the inflammatory burden, metabolic state and immune level of a cancer cachexia patient, can provide more accurate survival prognosis prediction compared with traditional indexes, and the parameters, such as creatinine, C-reactive protein to albumin ratio, contained in the CCAR index are all common blood examination items in clinical practice, so that the CCAR index is convenient to obtain and can be widely applied in clinical practice.

This invention relates to a group of extracellular vesicle-derived biomarkers for gastrointestinal malignancies and their applications, belonging to the field of molecular biology. The biomarkers of this invention are derived from extracellular vesicles and include proteins CALR, SPP1, OLFM4, and OIT3. When used for the diagnosis of gastrointestinal cancers, these biomarkers have shown good diagnostic efficacy, superior to existing serum biomarkers. Furthermore, the biomarkers of this invention show significant elevations in the early stages of gastrointestinal cancer, which is beneficial for early screening and diagnosis of gastrointestinal cancers.

This invention belongs to the field of animal model analysis technology, specifically relating to a method for establishing a model of gouty rheumatic fever subtypes, the application of a biomarker group, and a detection method. This invention constructs two subtype models of gouty rheumatic fever with more emphasis on dampness and fever with more emphasis on dampness, and establishes a UPLC-MS detection method for serum biomarkers, obtaining a biomarker group including lauroylcarnitine, taurine, palmitoyl-L-carnitine, L-leucine, leukotriene A4, and 13-Oxo-9,11-tridecadienoic acid. Studies show that this biomarker group can simply and effectively distinguish between gouty rheumatic fever with more emphasis on dampness and fever with more emphasis on dampness, and determine the success of model establishment for the two subtypes. Therefore, it can replace conventional characterization and biochemical pathological evaluation methods, improving the objectivity and operability of the assessment.

This invention provides a combination of serum biomarkers for the diagnosis of gastric cancer and their applications. This invention is the first to discover that CHI3L1, FCGBP, TFF2, and VSIG2 are significantly elevated in the serum of gastric cancer patients. ROC curve analysis verified that the combination of these four proteins as serum biomarkers can effectively distinguish between gastric cancer patients and healthy controls, and that combined use can better differentiate between early and late-stage gastric cancer patients, demonstrating superior diagnostic value for gastric cancer. Compared with traditional methods for gastric cancer diagnosis, the serum biomarker combination established in this invention is non-invasive, improving the accuracy of gastric cancer diagnosis. It can be used as a health screening test and provides an efficient and non-invasive detection method for gastric cancer patients who cannot undergo pathological examination.

The application relates to the technical field of disease detection, in particular to a biomarker for tumor detection, wherein the biomarker comprises at least one of mir-195-3p, mir-10b-5p, mir-133a-3p, mir-195-5p and mir-155-3p. The serum biomarker panel (mir-10b-5p, mir-133a-3p, mir-195-5p, mir-195-3p and mir-155-3p) composed of five miRNAs determined in the application provides a hope for early, non-invasive and accurate diagnosis of BC.

The application discloses an animal model construction method simulating human ischemic heart failure, and relates to the field of biomedical experimental animal models, and comprises the following steps: S1, model construction: embolism suspension liquid containing microspheres with a specific diameter is injected into the left ventricular cavity of a target animal through percutaneous puncture, so that the microspheres are embolized in myocardial microvessels through coronary artery circulation, thereby establishing a coronary artery microembolism model; S2, early screening: within 24 hours after model construction, cardiac ultrasound detection and serum biomarker detection are performed on the target animal; the animal model construction method simulating human ischemic heart failure simulates embolism of human myocardial arterioles and capillary arterioles by controlling the particle size (15-45 mu m) of the microspheres, induces diffuse myocardial ischemia closer to the clinic, thereby stably leading to progressive ventricular remodeling and chronic heart failure, rather than acute transmural infarction.