19 results about "Crohns diseases" patented technology

The invention discloses a Crohn disease focus automatic segmentation and activity evaluation system based on deep learning, which belongs to the field of medical artificial intelligence and comprises a data preprocessing unit, a focus automatic segmentation unit, a radiomics feature extraction unit, a feature screening and dimension reduction unit and an activity classification unit. According to the method, an nnU-Net deep learning segmentation model is combined with image omics feature extraction, multi-stage feature screening and machine learning classification technologies, so that full-process automation from CTE image preprocessing, focus automatic segmentation, feature extraction and screening to activity classification is realized. The system can efficiently and accurately segment the focus of Crohn's disease, automatically assesses the disease activity based on the screened key radiomics characteristics, significantly improves the consistency, objectivity and efficiency of diagnosis, and is suitable for clinical auxiliary diagnosis and scientific research analysis.

The invention provides a clostridium difficile infection and recurrent infection prediction model construction system, a storage medium and a kit, and the method comprises the steps: collecting an excrement sample of a Crohn disease subject through a collection module, and obtaining the genus-level relative abundance information of a flora genus level; the feature selection module adopts an LEfSe and Lasso feature screening algorithm to screen out a feature bacterial genus set; the training module is used for training prediction models by using an ElasticNet method based on genus-level relative abundance information of the characteristic bacterial genus set; the identification module obtains genus-level relative abundance information of a characteristic bacterium genus set of an individual to be tested and inputs the genus-level relative abundance information into the trained prediction model to obtain a risk score, and the prediction ability shows excellent sensitivity, specificity and accuracy in a training set and an independent test set.

The embodiment of the invention discloses a Crohn disease longitudinal queue course prediction system based on time perception Transform, and relates to the technical field of medical data processing, the system comprises a data preprocessing module, an input embedding layer, a Transform encoder and a multi-task multi-time window prediction header, the system breaks through the limitation that only baseline data is used for prediction of a traditional model, and the prediction efficiency is improved. According to the method, the full-cycle longitudinal data (such as inflammation indexes and medication records of each treatment) of the patient from the morbidity to the prediction can be integrated, and the disease progress, operation and medication risks of 1 year / 3 years / 5 years can be dynamically output. And reference is provided for clinicians.

One method for treating Crohn's disease in a patient involves administering a specific antibody against IL-23, for example, guselkumab, in an initial subcutaneous dose and subsequent subcutaneous doses so that the patient responds to the antibody and meets one or more of the clinical objectives.

The invention relates to a Crohn disease auxiliary prediction method based on machine learning. The method comprises the following steps: obtaining related prediction data of a user; whether missing items exist in the user related prediction data is judged, if yes, an alarm is given to remind a user to supplement, if the user confirms that supplement cannot be carried out, self-adaptive complementation is carried out, and finally to-be-predicted data is formed; inputting the to-be-predicted data into a pre-established Crohn disease auxiliary prediction model, and outputting a prediction result by the Crohn disease auxiliary prediction model; the Crohn disease auxiliary prediction model is constructed based on an XGBoost model; and visually displaying the prediction result to inform a user. According to the method, when the data input by the user is missing, the user can be reminded to supplement, if the data cannot be supplemented, self-adaptive complementation is carried out, the prediction accuracy of the model is improved, Crohn disease risk prediction can be carried out according to the existing indexes of the patient, the user can conveniently find related risks in time, and the user experience is improved. And the diagnosis and treatment efficiency of the user is improved.

The invention discloses an intelligent diagnosis system and method for Crohn disease muscular layer change, and belongs to the technical field of medical image analysis and artificial intelligence, and the system comprises an image collection and processing module which is used for receiving an MRI image of a patient, carrying out the de-noising and enhanced comparison, providing high-quality image data for the subsequent scoring analysis, and carrying out the calculation of the image data based on a preset algorithm, automatically sketching a target area; the image feature extraction module is used for extracting 102 radiomics features from the T1 enhanced image by using a Pyradiomics tool, and combining DCE-MRI functional parameters and conventional magnetic resonance parameters; the clinical data integration module is used for integrating clinical indexes of patients and constructing a multi-dimensional feature pool; and the score calculation module is used for calculating the extracted features. According to the intelligent diagnosis system and method for the Crohn disease muscular layer change, scientific research development can be promoted, an innovative muscular layer change evaluation scheme provides reliable data support for further scientific research, and the research progress in the field can be promoted.

The invention provides a Crohn disease early screening marker based on plasma proteomics. The early screening marker comprises the following nine proteins: CD274, CHI 3L1, REG1B, ITGAV, PRSS8, ITGA11, GDF15, DEFA1DEFA1B and IL6. The early screening marker provided by the invention can accurately and non-invasively predict CD as long as 16 years before diagnosis, which provides an important value for early screening of CD high risk groups and formulation of intervention measures. The invention also provides application of the Crohn disease early screening marker and an early screening kit for Crohn disease prediction.

The present invention provides a prediction model construction system, storage medium and kit for the occurrence of Clostridium difficile infection and recurrent infection. The collection module collects fecal samples from Crohn's disease subjects to obtain genus-level relative abundance information at the genus level of the bacterial flora; the feature selection module uses LEfSe and Lasso feature screening algorithms to screen out characteristic bacterial genus sets; the training module uses the ElasticNet method to train the prediction models based on the genus-level relative abundance information of the characteristic bacterial genus sets; the recognition module obtains the genus-level relative abundance information of the characteristic bacterial genus sets of the individual to be tested, and inputs the trained prediction model to obtain a risk score. The prediction ability shows excellent sensitivity, specificity and accuracy in both the training set and the independent test set.

To provide a suitable means for delivering a therapeutic biomolecule to a patient, wherein a stable and therapeutically effective blood level of the biomolecule occurs in a stable and convenient form over an extended period of time.SOLUTION: Provided is a device for treating a disease in a subject, wherein the subject may have Crohn's disease, ulcerative colitis, primary sclerosing cholangitis, eosinophilic esophagitis, autoimmune hepatitis, the device comprising a cell chamber comprising a population of cells that secrete a biomolecule for delivery to the subject.SELECTED DRAWING: None

The invention relates to the field of medical image analysis, in particular to an intestinal ultrasonic prediction system based on a machine learning model, which comprises a data acquisition module, a feature processing module, a feature screening module, a prediction model module, a result evaluation module and a clinical decision support module. Extracting visual interpretation features and radiomics features from the ultrasonic image, and integrating clinical information to form multi-dimensional feature data; after feature screening, a full-connection deep neural network based on an attention mechanism is constructed based on key features and is used for predicting the mucous membrane healing condition of a patient after the patient is treated by using the Usterinum monoclonal antibody. According to the method, early transmural response and transmural healing are introduced as prediction indexes, and accurate prediction of the treatment effect of the patient suffering from the Crohn disease is achieved; through multi-dimensional feature fusion and an attention mechanism, the prediction accuracy is remarkably improved; the treatment effect of the patient suffering from the Crohn disease is non-invasively evaluated, and the medical cost is reduced.

The invention provides a traditional Chinese medicine composition for treating Crohn disease anal fistula and a gel prepared from the traditional Chinese medicine composition. The traditional Chinese medicine composition is prepared from the following raw material medicines: dragon's blood, myrrh, abelmoschus manihot flowers, golden cypress, rhizoma bletillae, scutellaria baicalensis, angelica sinensis, radix angelicae and centella asiatica. The traditional Chinese medicine composition disclosed by the invention has multiple effects, can relieve immune inflammatory response related to neutrophil, effectively inhibits epithelial-mesenchymal transition, and treats Crohn disease anal fistula from source causes. The gel can be delivered to a deep fistula focus and retained, the local drug concentration is remarkably improved, and the long-acting effect is achieved. According to the invention, the closing rate of the fistula is improved, and the clinical application value is remarkable.

The invention relates to the technical field of biological medicines, and particularly discloses a biomarker composition and application thereof in predicting the risk of Crohn's disease. The reagent is at least used for detecting more than one group of biomarkers in a first group, a second group and a third group, the first group of biomarkers at least comprises two of APOC1, CDH13, CNDP1, CPB2, MEGF8 and RARRES1, the second group of biomarkers at least comprises two of ALAD, ENPP2, ITIH4, NAV2, PRG2 and SLIT2, and the third group of biomarkers at least comprises two of CFP, GLIPR2, IGHV3-13, PRDX1, SIAE and SNX25. Predictive and / or diagnostic kits developed based on these biomarkers can distinguish healthy individuals, preclinical, early and progression Crohn's disease risks.

The present invention relates in general to the treatment of Crohn's disease with an anti-IL-23p19 antibody, in particular to dosage regimens for the treatment of the disease.

Contemplated test kits and methods for food sensitivity are based on rational-based selection of food preparations with established discriminatory p-value. Particularly preferred kits include those with a minimum number of food preparations that have an average discriminatory p-value of ≤0.07 as determined by their raw p-value or an average discriminatory p-value of ≤0.10 as determined by FDR multiplicity adjusted p-value. In further contemplated aspects, compositions and methods for food sensitivity are also stratified by gender to further enhance predictive value.

The present invention discloses a Crohn's disease diagnosis auxiliary system based on a flexible endoscope, comprising: a database for storing sample sets of various parts of the intestine under different pressure states; an image acquisition module for acquiring images of the intestine under natural pressure states, and acquiring images of the intestine under different pressure states according to preset rules; an auxiliary analysis module for comparing the images acquired by the image acquisition module with sample sets of corresponding pressure states in the database, and outputting a judgment result; the preset rule is to judge whether to acquire images of the intestine under different pressure states based on the results of the auxiliary analysis module's analysis of the images under natural pressure states; by acquiring images under different pressure states, analyzing and comparing the images under different pressure states with the corresponding samples in the database, and making a comprehensive judgment, the accuracy of Crohn's disease diagnosis can be improved.

A device and method for minimizing asthma and / or Crohn's or IBD. The device comprises a user-wearable device comprising: a micro-electro-mechanical systems (MEMS) microphone system; a bioelectrical impedance analysis system; a breath humidity and breath temperature sensor system; an interstitial fluid monitoring system; at least one processor; a power system that powers the at least one processor, the at least one electronic communications system, and the systems of the user-wearable device; and wherein the electronic communication system may receive data from at least one other electronic system that carries instructions for a treatment plan that is refined over time via machine learning.

High-concentration risankizumab formulations. This description relates to novel antibody formulations comprising risankizumab at a high concentration. This description further relates to methods of using these formulations for the treatment of diseases (e.g., psoriasis and Crohn's disease).

Compounds of Formula (II), pharmaceutical compositions containing them, methods of making them, and methods of using them including methods for treating disease states, disorders, and conditions associated with the cGAS pathway, such as autoimmune disorders including Aicardi-Goutieres Syndrome (AGS), Systemic Lupus Erythematosus (SLE), Lupus Nephritis, Scleroderma, Sjogren's Syndrome, Inflammatory Myopathies, Hidradenitis Supperativa (HS), Parkinson's Disease, Rheumatoid Arthritis, Ulcerative Colitis and Crohn's Disease,wherein Ra, {circle around (A)}, R1 and R2, are defined herein.