140 results about "Clinical disease" patented technology

The invention discloses an adverse drug reaction event recognition method and system based on multivariate knowledge mixed retrieval enhancement, and the method comprises the steps: extracting drug entities from a to-be-recognized clinical disease course record, segmenting the disease course record, and obtaining a drug entity set and a sentence set; for each extracted drug entity, retrieving drug concept knowledge having a hyponymy relationship with the drug entity and drug adverse reaction knowledge having an adverse reaction relationship with the drug entity in a pre-constructed multivariate knowledge base; for each sentence obtained through segmentation, searching suspected adverse drug reaction events meeting a first similarity requirement and drug field text knowledge meeting a second similarity requirement in a pre-constructed multivariate knowledge base; and finally, calling a large language model, taking all the retrieved knowledge as reference knowledge, and identifying the adverse drug reaction event from the to-be-identified clinical disease course record. According to the invention, the accuracy and reliability of adverse drug reaction event identification can be improved.

The invention relates to the technical field of model construction, in particular to a method for creating an image recognition model based on clinical disease data integration. The method comprises the following steps: acquiring a medical clinical orthopedic image set; the bone density and the bone form of the medical clinical orthopedic image set are extracted, bone structure division is carried out on the medical clinical orthopedic image set, bone structure division images are generated, and the bone structure division images comprise large bone structure images and small bone structure images; analyzing the bone layer thickness of the big bone structure image and performing physical layer thickness compensation reconstruction on the big bone structure image to generate big bone middle virtual slice data; and performing detail guide reconstruction on the small bone structure image to generate small bone fracture texture reconstruction data. According to the invention, through image resolution enhancement, multi-modal data integration, motion simulation and optimization model training, the accuracy of skeleton image dynamic identification is improved.

The invention relates to the technical field of intelligent evaluation, in particular to a novel multi-modal Alzheimer's disease early cognitive function intelligent evaluation method, which comprises the steps of multi-modal data collection, data processing and feature extraction, and cognitive evaluation model construction. By collecting image data, facial recognition, linguistic and acoustic characteristics, exhaled gas components and eye movement and gait data under a double-task normal form, multi-aspect physiological and cognitive information of a patient is comprehensively collected by adopting a multi-modal data collection technology, and multi-modal information of the patient is acquired through multi-modal data. The evaluation method can more comprehensively reflect the cognitive state of a patient, predicts and automatically identifies abnormal cognitive performance through the cognitive evaluation model, can significantly improve the diagnosis sensitivity and specificity of the early cognitive impairment of the Alzheimer's disease, overcomes the limitation of a traditional single-mode evaluation method, and has a good application prospect in the field of diagnosis of early cognitive impairment of the Alzheimer's disease. And early discovery and early intervention of clinical diseases are effectively supported.

The present invention relates to the technical field of dental medical treatment, and specifically discloses a method for using a CBCT (Cone Beam Computer Tomography) for automatically positioning a tooth, which comprises the following steps: S01, archiving CT data; S02, calculating AI and generating AI results; S03, entering CT reading by a client; S04, downloading and loading the CT data; S05, opening a function of a tooth lens; S06, selecting a corresponding tooth position in a tooth position list; and S07, selecting a 3D tooth rendering mode. The function of the ‘tooth lens’ is added into traditional CT reading, which is suitable for clinical disease diagnoses such as ‘tooth extraction, root canal therapy, tooth repair’ and the like in oral treatment, and doctors can precisely and quickly position the single tooth through selection for the tooth position, which facilitates more comprehensive analysis.

The invention discloses a Claudin18.2-targeting nano antibody and application thereof, and belongs to the technical field of molecular biology. Aiming at the unique advantages of a nano antibody in the prior art, the invention provides a nano antibody targeting Claudin18.2, the amino acid sequence of the targeting nano antibody is shown as SEQ ID NO.1, and the nano antibody has relatively strong affinity with Claudin18.2 positive cells 293T-Claudin18.2, and can be combined with Claudin18.2 protein expressed on the surfaces of the cells. The targeted Claudin18.2 nano antibody provided by the invention can be prepared through in-vitro engineering bacterium mass expression, can be applied to preparation of protein detection antibodies or therapeutic antibodies, can be used for in-vivo and in-vitro detection of tumor tissues expressed by Claudin18.2, and has important commercial value in clinical disease diagnosis and treatment.

The present invention uses ex vivo human airway cultures to assess the human transmissibility and replication competence of influenza and coronavirus strains. By comparing pandemic influenza A subtype H1N1 and highly pathogenic avian influenza H5N1 as reference strains, the transmissibility risk of various viruses was evaluated and categorized. Additionally, an in vitro model evaluated virus-induced impairment of alveolar fluid clearance (AFC) as an indicator of disease severity. The study revealed correlations between bronchus viral replication, human transmission, AFC impairment, and clinical disease severity across different influenza and coronavirus strains.

The invention provides construction and application of a multi-dimensional medical big data fusion and disease prediction recognition engine, and aims to fuse features of multi-dimensional medical data according to dimension weights through a pre-constructed factor group: F-F-form (q) so as to generate a targeted feature data set M (qt). And further performing prediction model training based on the feature data set M (qt), and putting the prediction model into clinical disease prediction application. Therefore, the fusion features are identified and learned through the model on the dimension weight, so that the learning efficiency of the model on the features is improved, the construction of the prediction model is accelerated, the application period of a clinical model is shortened, targeted disease prediction is performed by using the biased model generated by fusion, and disease prediction guidance in the clinical dimension is achieved.

According to the exosome multi-target detection method based on the nano-frame multi-satellite mode, a high-stability tetrahedron is used as a core skeleton, multiple high-protein-affinity nucleic acid aptamer tongs are assembled and matched according to needs to construct a high-reproducibility biomarker recognition element, a molecular form with multiple satellites wrapping exosome is constructed, and the exosome multi-target detection method based on the nano-frame multi-satellite mode is obtained. According to the method, a'free satellite 'element is formed, and flow cytometry is utilized to detect the particle size and output signals with ultralow background interference, so that multiple detection requirements of different tumors on different expression levels of different markers in different development processes can be met, and an identification-separation-detection integrated high-specificity exosome detection strategy is realized. Clinical examination and diagnosis requirements serve as fundamental guidance, detection potential is excavated on an existing basic flow platform, instrument detection particle size limitation is turned into background killer, a new instrument detection thought is widened, detection performance is improved, exosome encrypted information decoding is accelerated, and the transformation progress of clinical disease prevention and treatment and tumor diagnosis and treatment is promoted and guided.

The invention discloses a high-channel clinical microelectrode array intelligent brain function positioning system and method, and belongs to the field of electronic information and the technical field of clinical disease diagnosis and treatment. The system comprises a microelectrode array implanted in the brain, a signal processing and transmission unit and a signal identification unit. The microelectrode array adopts a multi-channel design, so that neural electrophysiological signals and transmitter chemical signals in different depths and directions can be synchronously detected, and the resolution ratio of a single cell level is achieved. The signal processing and transmission unit is responsible for signal acquisition, amplification and transmission and applying electrical stimulation; and the signal identification unit carries out real-time processing on the signal through a convolutional neural network algorithm, rapidly identifies a target nucleus and realizes accurate positioning. The nerve cell discharge and transmitter release can be monitored in real time at different depths and in different directions, rapid and accurate target spot positioning can be achieved by means of an advanced intelligent algorithm, and a more reliable basis is provided for DBS surgery.

The invention relates to a whole body organ metabolism network analysis method and device, equipment and a storage medium. The method comprises the steps that a PET image of a subject is collected, an SUV image, a Ki image and TAC data are obtained according to the PET image, and physiological information, clinical pathology information and daily habit information of the subject are collected; performing metabolism feature extraction based on the PET image, the SUV image and the Ki image corresponding to the region of interest, performing curve fitting on the TAC data of each organ by using the PET image, and representing metabolism disturbance under different organs by using a fitting residual error; constructing a whole body organ metabolism network according to the physiological information, the clinical pathological information, the daily habit information, the metabolic characteristics and the metabolic disturbance, and performing whole body organ metabolism analysis on the subject through the whole body organ metabolism network. According to the method, individualized differences are avoided, the metabolic association among organs of the whole body of a specific disease can be captured more comprehensively, and early diagnosis, accurate evaluation and individualized treatment of clinical diseases are facilitated.

The invention discloses a multi-dimensional quality cross validation evaluation method and system based on medical model training, and belongs to the technical field of medical file evaluation. Constructing a pathological feature sample library and a medical record archive library based on the pathological feature description words and the medical record archives, and classifying and recording the medical record archives through the pathological feature description words; according to the incidence process of the pathological characteristics, forming an incidence state transition relation chain and configuring incidence state verification nodes; in combination with a clinical pathology state time range of the pathology state verification node, screening associated cross-pathology features to form a cross-pathology label; and updating according to a verification node sequence to obtain a disease occurrence state cross relation chain, performing multi-dimensional quality evaluation on the medical record file, and outputting an evaluation value. According to the method, the accuracy and reliability of medical file quality evaluation are improved through multi-dimensional cross validation, high-quality medical record data support is provided for medical model training, and the method is suitable for medical record quality auditing, medical data treatment and medical model training data screening scenes of medical institutions at all levels.

The invention belongs to the technical field of antiviral microecological preparations for livestock and poultry, and particularly relates to bacillus amyloliquefaciens H-6 and application thereof in preparation of drugs for treating or preventing porcine reproductive and respiratory syndrome virus infection. The preservation number of the bacillus amyloliquefaciens is CCTCC (China Center for Type Culture Collection) NO: M 20242740. The bacterial strain can reduce the infection activity of PRRSV cells, inhibit invasion and infection of PRRSV to the cells, and reduce proliferation of viruses on the cells. The anti-infection research on the cell level and the animal body level shows that the strain has a remarkable PRRSV resisting effect in vivo and in vitro, proliferation of viruses in a pig body can be reduced, damage of PRRSV infection to lung tissues and organs is reduced, the adverse effect of PRRSV infection to the body is effectively controlled, clinical disease symptoms of the pig during PRRSV infection can be weakened, and the porcine reproductive and respiratory syndrome treatment effect is improved. The composition can be used for preventing and controlling the porcine reproductive and respiratory syndrome.

The invention uses ex vivo human airway cultures to assess the transmissibility and replication ability of influenza and coronavirus strains. By comparing the pandemic influenza A H1N1 and the highly pathogenic influenza A H5N1 as reference virus strains, the spreading risks of various viruses are evaluated and classified. In addition, an in vitro model is used to assess the degree of alveolar fluid clearance (AFC) impairment caused by the virus as an indicator of the severity of the disease. The research reveals the relevance among the virus replication ability, human transmission, AFC damage degree and clinical disease severity of different influenza and coronavirus strains in bronchus.

The application discloses a lumbar disc herniation postoperative recurrence risk prediction system based on domain offset correction, and relates to the technical field of medical data processing and clinical disease risk prediction. The system obtains the multi-modal clinical and imaging feature vectors and follow-up outcome data of a training queue and an independent verification queue, trains a central classifier to quantize and correct the multi-center data distribution difference, calculates and trims the importance weight of each training case, trains a survival analysis base learner based on the processed weight and performs stacked integration, determines a final deployment model in combination with an independent verification case queue, calls the final deployment model to perform reasoning on a target patient after lumbar disc herniation surgery, and outputs an individualized recurrence risk score, risk stratification and recurrence-free survival curve, thereby improving the robustness and reliability of the risk prediction system in a cross-center scenario, and being suitable for postoperative follow-up management of lumbar disc herniation and auxiliary clinical decision-making.

The invention discloses a herpes zoster skin lesion staging evaluation method and system based on AI image recognition, and relates to the technical field of herpes zoster skin lesion staging evaluation, and the method comprises the following steps: collecting herpes zoster skin lesion image data continuously recorded in multiple periods, synchronously embedding a time identifier in the collection process, and carrying out the time identification; recording the shooting moment, the illumination state and the shooting angle information of each frame of image in a unified manner to form an original image sequence; and based on the original image sequence, according to the progressive sequence of the time identifiers, performing adaptive sorting adjustment on the time intervals between the adjacent frames. According to the method, a stable skin lesion time evolution track is constructed through time identification and a continuous processing flow, so that staging reverse judgment caused by frame order disorder is avoided, and the continuity and reliability of herpes zoster skin lesion staging evaluation are improved; and meanwhile, color, area and texture changes are uniformly incorporated into natural time rhythm constraints, so that a staging result better conforms to a clinical disease course rule, and the safety of remote follow-up visit and intelligent evaluation is improved.

The present invention relates to a vaccine for the prevention or treatment of a Zika virus infection and / or a Zika virus associated clinical illness of any severity. Further provided are methods for producing and inactivating Zika virus as well as processes for manufacturing compositions comprising Zika virus.

The application discloses a high-channel clinical microelectrode array intelligent brain function positioning system and method, and belongs to the fields of electronic information and clinical disease diagnosis and treatment technologies. The system comprises a microelectrode array implanted in the brain, a signal processing and transmission unit and a signal identification unit. The microelectrode array adopts a multi-channel design, can synchronously detect neural electrophysiological signals and transmitter chemical signals of different depths and directions, and has a resolution of a single cell level. The signal processing and transmission unit is responsible for signal acquisition, amplification and transmission, and applies electrical stimulation; the signal identification unit performs real-time processing on the signals through a convolutional neural network algorithm, quickly identifies target nuclei, and realizes accurate positioning. The application can realize real-time monitoring of neural cell discharges and transmitter releases at different depths and different directions, and can realize rapid and accurate target positioning with the aid of advanced intelligent algorithms, thereby providing a more reliable basis for DBS surgery.

The present invention discloses an ultrasound / magnetic resonance dual-mode nanoprobe and its preparation method and application. The preparation method comprises the following steps: S1, preparing iron sulfide nanosheets (FeS) using ammonium ferrous sulfate, trisodium citrate, etc. as raw materials, and resuspending the FeS in ethanol to obtain an FeS ethanol solution; S2, adding perfluorohexane to the FeS anhydrous ethanol solution, and using an ultrasonic crusher under an ice bath to prepare a FeS / PFH suspension; S3, mixing the FeS / PFH suspension with a 1 mg / mL dopamine hydrochloride anhydrous ethanol solution, stirring at room temperature in the dark, and washing with pure water to obtain the final product, FeS / PFH / PDA nanomaterial. The present invention discloses an ultrasound / magnetic resonance dual-mode nanoprobe and its preparation method and application. The synthesis method for preparing the ultrasound / magnetic resonance dual-mode nanoprobe is simple and highly operable; the synthesized product is stable and reproducible, which is beneficial for biomedical research and clinical disease diagnosis.

The invention belongs to the technical field of mass spectrum ionization sources, provides a tandem mass spectrum ionization source for online detection of disease markers in tail end gas of expired gas of a human body, and aims to solve the problems of complex expired gas sampling, insufficient detection sensitivity and difficult real-time monitoring in the prior art. According to the ionization source device, real-time online expiration analysis of expired gas of a human body can be achieved, the expired gas end gas moment can be determined according to the change of the concentration of carbon dioxide in the expired gas, and therefore real-time analysis of disease markers in the expired gas end gas is achieved. According to the technical scheme, the design that double ionization sources are connected in series is adopted, and a funnel-shaped chemical ionization source is arranged at the front end and specially used for high-sensitivity detection of volatile organic compounds in exhaled air; the photoelectron ionization source is arranged at the rear end and used for monitoring the carbon dioxide concentration in real time and determining the end gas moment. According to the design, high sensitivity of organic matter detection and accurate monitoring of carbon dioxide concentration are both considered in a partitioned ionization mode. The efficient, sensitive and reliable mass spectrum ionization source device is provided for exhaled gas detection, automatic distinguishing of the front end and the tail end of exhaled gas and high-sensitivity analysis of disease markers in tail end gas can be achieved, the sampling process can be simplified, the detection efficiency can be improved, and the mass spectrum ionization source device has wide application prospects, can be suitable for various scenes and has wide application prospects. The method includes clinical disease early diagnosis, health monitoring and the like.

The application relates to a whole-body organ metabolism network analysis method, device, equipment and storage medium. The method comprises the following steps: collecting a PET image of a subject, obtaining SUV images, Ki images and TAC data according to the PET image, and collecting physiological information, clinical pathology information and daily habit information of the subject; metabolism characteristics are extracted based on the PET images, SUV images and Ki images corresponding to the region of interest; the TAC data of each organ is curve-fitted by using the PET image, and the metabolism disturbance under different organs is represented by using the fitting residual error; a whole-body organ metabolism network is constructed according to the physiological information, clinical pathology information, daily habit information, metabolism characteristics and metabolism disturbance; and the whole-body organ metabolism of the subject is analyzed through the whole-body organ metabolism network. The application avoids individual differences, can more comprehensively capture the metabolism correlation among whole-body organs of a specific disease, and is helpful for early diagnosis, accurate evaluation and individualized treatment of clinical diseases.

The invention discloses a fibroblast preparation and a preparation method and application thereof, and belongs to the technical field of biomedical engineering, and the fibroblast preparation is prepared by mixing and compounding fibroblasts, a carrier and an active substance solution. The preparation method comprises the following steps: S1, cell pretreatment; s2, preparing a cross-linked collagen fiber hydrogel; s3, preparing an active substance solution; and S4, preparing the fibroblast preparation. By pretreating fibroblasts, activating the anti-inflammatory phenotype of the fibroblasts, promoting the fibroblasts to secrete collagen, loading the cells through collagenous fiber hydrogel and adding active substances, the skin lesion is repaired, meanwhile, type II immune excessive activation is inhibited, and the clinical disease performance of eczema mice is remarkably improved. The problems of limited skin disease treatment and skin lesion repair effects caused by low cell survival rate, poor carrier biocompatibility and poor active substance synergism in the prior art are solved, and the preparation method has the potential of preparing drugs for treating skin diseases.

The invention belongs to the technical field of antiviral drugs for livestock and poultry, and discloses application of lysophosphatidylcholine and dihydromyricetin in preparation of drugs for treating or preventing porcine reproductive and respiratory syndrome virus infection. The CAS number of the lysophosphatidylcholine is 17364 to 16 to 8, and the CAS number of the dihydromyricetin is 27200 to 12 to 0. The applicant performs cell level and animal body level anti-infection research on the pharmaceutical composition, and finds that the pharmaceutical composition shows a remarkable anti-PRRSV effect in vivo and in vitro, can reduce proliferation of viruses in a pig body, reduces damage of PRRSV infection to lung tissues and organs, effectively controls adverse effects of PRRSV infection to the body, and has a remarkable anti-PRRSV effect. The clinical disease symptoms of the pigs in the PRRSV infection period can be weakened, and the porcine reproductive and respiratory syndrome can be prevented and controlled.

In one aspect, the disclosure relates to relates to substituted benzothiophene analogs which are useful as selective degraders of estrogen receptor, methods of making same, pharmaceutical compositions comprising same, and methods of treating one or more clinical conditions associated with estrogen receptor, such as a cancer, including breast cancer, or osteoporosis. 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 disclosure.

The present invention relates to the field of model construction technology, and in particular to a method for creating an image recognition model based on clinical disease data integration. The method comprises the following steps: acquiring a medical clinical orthopedic image set; extracting bone density and bone morphology from the medical clinical orthopedic image set and performing bone structure segmentation on the medical clinical orthopedic image set to generate a bone structure segmentation image, wherein the bone structure segmentation image includes a large bone structure image and a small bone structure image; analyzing the bone layer thickness of the large bone structure image and performing physical layer thickness compensation reconstruction on the large bone structure image to generate large bone intermediate virtual slice data; performing detail-guided reconstruction on the small bone structure image to generate small bone fracture texture reconstruction data. The present invention improves the accuracy of dynamic bone image recognition by enhancing image resolution, integrating multimodal data, performing motion simulation, and optimizing model training.

The Great Cerebral Vein, or Vein of Galen is comprised of a unique structure having a location which both implicates it in various clinical conditions, and can be treated by systems which, for example, go around corners of the Transverse and Straight sinuses for minimally invasive therapy embedded in the Vein of Galen the present inventions constitute progress in science and the useful arts worthy of protection as US Letters patent as novel.

The application discloses a nanobody targeting Claudin 18.2 and an application thereof, and belongs to the technical field of molecular biology. In view of the unique advantages of the nanobody in the prior art, the application provides a nanobody targeting Claudin 18.2, wherein the amino acid sequence of the nanobody is shown as SEQ ID NO. 1; the nanobody has strong affinity to 293T-Claudin 18.2 positive cells and can be combined with the Claudin 18.2 protein expressed on the cell surface. The nanobody targeting Claudin 18.2 provided by the application can be prepared by large-scale expression of an in-vitro engineering bacterium, can be applied to preparation of a protein detection antibody or a therapeutic antibody, can be used for in-vitro and in-vivo detection of tumor tissues expressing Claudin 18.2, and has important commercial value in clinical disease diagnosis and treatment.

The invention discloses application of RNFT1 protein as a triple negative breast cancer treatment target. According to the present invention, the E3 ligase RNFT1 is derived from the IP binding protein spectrum detection result of the membrane protein PDL1, and the influence of the RNFT1 on the PDL1 protein can be significantly observed through the RNFT1 overexpression and knock-down. Through flow and Western Blot, the reliability and importance of RNFT1 as a regulation target spot on the stability of the immune checkpoint PDL1 protein can be judged. Animal experiments show that high expression of the RNFT1 is unfavorable for immunotherapy response, and the curative effect of chemotherapy and immunotherapy is reduced, so that powerful evidence can be provided for evaluating the curative effect of immunotherapy by taking the RNFT1 as a predictive index and applying the RNFT1 as a drug of an immunotherapy target spot. RNFT1 plays an important role in regulating and controlling the stability of PDL1 protein on the surface of a cell membrane, and possibly becomes a specific marker for predicting the immunotherapy effect of triple-negative breast cancer, and the discovery possibly provides a basis for the development of new drugs for clinical diseases.

The application discloses a nanobody targeting mesothelin and application thereof, and belongs to the technical field of molecular biology. In view of the unique advantages of nanobodies in the prior art, the application provides a nanobody targeting mesothelin, wherein the nanobody targeting mesothelin comprises CDR1 as shown in SEQ ID NO. 1, CDR2 as shown in SEQ ID NO. 2 and CDR3 as shown in SEQ ID NO. 3. The nanobody targeting mesothelin has strong binding force with cells overexpressing mesothelin. It can be seen that the nanobody targeting mesothelin can bind to mesothelin protein expressed on the surface of cells, and can be applied to preparation of a protein detection antibody or a therapeutic antibody, and has important commercial value in clinical disease diagnosis and treatment.

The invention discloses a biological age assessment method and system based on full life cycle DNA methylation and application, and belongs to the technical field of bioinformatics. The method comprises the following steps: firstly, carrying out quality control and standardization treatment on obtained original DNA methylation data; then, screening differential methylation sites significantly related to calendar age as features; then, by taking calendar age as a target variable, constructing a regression model by adopting a LightGBM gradient lifting framework to obtain a methylated clock model; then, predicting the DNA methylation age of the individual by using the model, and calculating an epigenetic age acceleration value based on the deviation between the DNA methylation age and the calendar age; and finally, carrying out correlation analysis on the age acceleration value and health or physiological indexes of different life stages, so as to evaluate the biological aging state of the individual and predict related health risks. The method covers the whole life cycle, is suitable for Chinese population, and can provide an effective tool for clinical disease risk prediction, health management and anti-aging intervention effect evaluation.

This invention discloses a conductive hydrogel, its preparation method, and its applications. The conductive hydrogel's raw materials include hydroxypropyl cellulose, hyaluronic acid, acrylamide, and a conductive agent; the conductive agent includes at least one selected from lithium chloride, potassium chloride, sodium chloride, sodium sulfate, and potassium sulfate. This conductive hydrogel utilizes the liquid-phase transition characteristics of hydroxypropyl cellulose, combined with acrylamide, hyaluronic acid, and lithium chloride to achieve respiratory and body temperature monitoring. This conductive hydrogel exhibits good conductivity and can detect different types of respiration, providing valuable monitoring for the monitoring and development of clinical diseases. Simultaneously, the synergistic effect of the combined hyaluronic acid, acrylamide, and lithium chloride adjusts the lower critical dissolution temperature of hydroxypropyl cellulose to 37°C, causing the hydrogel to change from transparent to opaque at 37°C, enabling real-time temperature and respiratory monitoring for febrile patients in clinical settings.