101 results about "Diagnoses diseases" patented technology

Systems and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular disease, cancer, neurological disorders, immune system disorders and genetic diseases.

The invention discloses a primer probe group and a kit for joint detection of mycoplasma genitalium, ureaplasma urealyticum and chlamydia trachomatis, and belongs to the technical field of molecular biological detection. The primer probe group comprises a primer probe group A for directly detecting a mycoplasma genitalium mgpB gene, a primer probe group B for directly detecting a ureaplasma urealyticum ureB gene and a primer probe group C for directly detecting a chlamydia trachomatis ompA gene; the kit comprises a PCR (Polymerase Chain Reaction) reaction solution and the primer probe group. Nucleic acid extraction is not needed, the detection cost is greatly reduced, the experiment time is shortened, meanwhile, the specificity and accuracy are still guaranteed, meanwhile, the sensitivity is improved, and the method has wide application prospects in the fields of non-gonococcal genital tract infection main pathogen detection, infertility and prenatal and postnatal care screening and the like. And the kit has important significance on clinical diagnosis, early treatment and prevention of diseases, prevalence and the like.

The present invention relates to MSLN-specific binding constructs comprising a designed ankyrin repeat domain with binding specificity for MSLN and a chelator capable of bonding to a radionuclide, as well as to such MSLN-specific binding constructs comprising a half-life extending moiety with binding specificity for serum albumin. The invention further relates to methods of producing such radio-labelled MSLN-specific binding constructs, pharmaceutical compositions comprising such constructs, and the use of such constructs or pharmaceutical compositions in methods for treating, imaging or diagnosing diseases, such as cancer.

The invention relates to the technical field of medical systems, in particular to an intelligent diagnosis auxiliary system based on informatization planning, which comprehensively collects inspection operation parameters and patient physique information and covers data in multiple aspects from inspection process details to patient individual physique characteristics. The data are mapped to a test method-interference factor relation network through a knowledge graph, the influence of test operation interference and patient physique interference on diagnosis can be comprehensively analyzed, the influence condition of interference parameters is quantified by adopting a natural constant power formula in test process anomaly analysis and physique-to-diagnosis disease anomaly influence analysis, and the diagnosis accuracy is improved. The non-linear quantification mode better accords with the actual relation between interference and influence in a medical examination operation scene, the influence degree of the examination process and the patient physique on diagnosis can be more accurately evaluated, and then a more reliable basis is provided for diagnosis.

The embodiment of the invention provides a multi-role adaptive interaction method and system based on a stomatology knowledge base, and the method comprises the steps: recognizing a query role when a query signal is received, and obtaining the query content; calling a preset query engine matched with the query role, accessing a pre-constructed knowledge base according to the currently called query engine and the query content, and obtaining a differential diagnosis set containing a plurality of diseases with a sorting relationship; and performing multi-dimensional differential diagnosis reasoning on the diseases in the differential diagnosis set one by one according to the sorting relationship, correspondingly evaluating the comprehensive confidence coefficient of the reasoning result, and when the comprehensive confidence coefficient is not less than a preset threshold value, taking the corresponding disease as a diagnosis disease, and outputting a query report matched with the query role. According to the invention, doctors can be assisted to make professional clinical decisions, and convenient oral common sense popularization services can be provided for patients.

The present invention relates to a system and a device for diagnosing disease by using artificial intelligence, and an operating method thereof. The method may comprise the steps of: acquiring an interpretation report in which interpretation results of a medical image is recorded in a non-standardized form, a prompt including a user request to be input into an artificial intelligence model for disease diagnosis, and a template for standardizing and storing information necessary for the disease diagnosis; generating, on the basis of the prompt, the template and the interpretation, report input information for diagnosing the medical image; extracting diagnosis information necessary for the disease diagnosis from the input information; recording the extracted diagnosis information in the template; transmitting the diagnosis information recorded in the template to a designated server including the artificial intelligence model; receiving diagnosis results of the medical image from the server; and providing the received diagnosis result. The present invention can improve the speed, accuracy and / or objectivity of disease diagnosis. In addition, the present invention can provide an effective treatment method on the basis of the diagnosis results. Therefore, the present invention can improve the efficiency of disease diagnosis.

Anti-4-1BB single domain antibodies and polypeptides, e.g., bispecific antibodies and chimeric antigen receptors comprising these single domain antibodies, are provided. These antibodies, including humanized antibodies, exhibit superior activity and are suitable for use in various bispecific antibody formats. Methods of using the antibodies or polypeptides to treat and diagnose diseases, e.g., cancer, are also provided.

The all-in-one cartridge (100) for on-site diagnosis provided in the present disclosure relates to an integrated cartridge capable of sample solution injection and detection. The cartridge is equipped with a sample injection cap (13), a sample injection port (14), a tip (12), a 2D barcode (15), a sample chamber (22), a buffer chamber (23), a mixing chamber (25), a washing chamber (26), and a PCR chamber (28) for performing PCR. The cartridge (100) can be used for molecular diagnosis, and a diagnostic device therefor can be selectively used for molecular diagnosis, immunodiagnosis and rapid diagnosis.

Systems and methods for diagnosing a disease, a condition, or a characteristic in a subject are provided. In one such method, a future severity of an infection or inflammatory disease in a subject afflicted with the infection or inflammatory disease is predicted by obtaining a plurality of methylation levels. Each respective methylation level in the plurality of methylation levels represents a corresponding methylation level at a CpG site at a corresponding genetic locus in a plurality of genetic loci in a biological sample obtained from the subject. The plurality of methylation levels are inputted into a model comprising a plurality of parameters, where the model applies the plurality of parameters to the plurality of methylation levels to generate as output from the model an indication as to future severity of an infection or inflammatory disease in the subject.

Protein scaffolds and scaffold libraries based on a fibronectin type III (FN3) domain with an alternative binding surface design, isolated nucleic acids encoding the protein scaffolds, vectors, host cells, methods of making thereof, and uses as therapeutic molecules for treatment and diagnosis of diseases and disorders.

A method of diagnosing an infectious disease, including determining the severity of the disease, in a subject comprising measuring an expression level of at least one protein selected from the group consisting of TSG-14, AGER, ANG-2 and ST2 in a sample of the subject; and diagnosing the disease based on said expression level. Kits for carrying out the diagnosis are also disclosed.

There is a challenge in that doctors, hospitals, insurance companies, or patients cannot obtain the necessary medical information in a timely manner when they need it. Therefore, by providing patients with up-to-date digital medical records that can be securely accessed from anywhere, we can strengthen collaboration and communication among different healthcare providers and institutions. [Solution] This is solved by an AI system, method, and computer program product for patient diagnosis and treatment suggestion, which uses advanced AI algorithms to analyze all available data to diagnose diseases and suggest treatments.

A clinical evaluation system and method are disclosed that facilitate the use of one or more conduction deviation features or parameters determined from biophysical signals such as cardiac or biopotentials signals. Conduction derivation features or parameters may include VD conduction derivation features or parameters and / or VD conduction derivation Poincaré features or parameters. The conduction derivation features or parameters can be used in a model or classifier (e.g., a machine-learned classifier) to estimate metrics associated with the physiological state of a patient, including for the presence or non-presence of a disease, a medical condition, or an indication of either. The estimated metric may be used to assist a physician or other healthcare provider in diagnosing the presence or non-presence and / or severity and / or localization of diseases or conditions or in the treatment of said diseases or conditions.

An apparatus for diagnosing a disease and a method for diagnosing a disease, in which: a plurality of voice signals are received to generate a first image signal and a second image signal which are image signals for each voice signal; a plurality of disease probability information for a target disease causing a voice change are extracted by using an artificial intelligence model determined according to the type of each voice signal and a generation method used to generate each image signal for the first image signal and the second image signal for each voice signal; and it is determined whether the target disease is negative or positive on the basis of the plurality of disease probability information.

The present disclosure relates to a method of isolating extracellular vesicles directly from human tissues. The invention further relates to a method of identifying disease and tissue specific membrane proteins on extracellular vesicles by membrane isolation and proteomic analysis. The invention further relates to methods of diagnosing diseases by capturing extracellular vesicles by the use of disease specific membrane proteins from body fluids, and detecting or analyzing molecular signatures (proteome, DNA, and RNA) on captured extracellular vesicles. Moreover, the present invention relates to kits, apparatus and software required for implementing aforementioned methods.

A method of detecting disease through analysis of hair images can indicate specific diseases is an intriguing topic intersecting dermatology, diagnostic medicine, and technology. By obtaining a hair from the body and analyzing images for fungus as an indicator of various health conditions. Disclosed herein is a methods relating to the classification of hair samples which can be used to identify and to diagnose conditions or to support treatment-related decisions.

The invention relates to a method for diagnosis, disease monitoring and / or therapy guidance in a patient suspected of having a neurodegenerative disease of the Frontotemporal Dementia-Amyotrophic Lateral Sclerosis-spectrum (FTD-ALS-spectrum), comprising (a.) providing a sample obtained from said patient, wherein said sample comprises extracellular vesicles, (b.) determining a level of one or more FTD-ALS-spectrum biomarkers in the extracellular vesicles of said sample, (c.) wherein the level of the one or more biomarkers is indicative of whether the patient has (and / or allows to distinguish between) a neurodegenerative disease of the FTD-ALS-spectrum comprising a Tau-proteinopathy or a neurodegenerative disease of the FTD-ALS-spectrum comprising a TAR DNA-binding protein 43 (TPD-43)-proteinopathy. The invention further relates to a kit for carrying out the method of the present invention, methods of treating patients identified using the method of the invention, methods of determining said FTD-ALS-spectrum biomarkers in the extracellular vesicles of said sample, and samples comprising extracellular vesicles and said FTD-ALS-spectrum biomarkers.

The invention provides an electrocardio diagnosis method and system based on a large language model, and the method comprises the steps: extracting a plurality of electrocardio features from a to-be-diagnosed electrocardio signal based on the knowledge of electrocardio diagnosis diseases; inputting the electrocardiosignal to be diagnosed into a preset electrocardiograph time sequence model for electrocardiograph waveform analysis to obtain a first diagnosis tag and a diagnosis probability corresponding to the first diagnosis tag; searching a historical electrocardiosignal similar to the electrocardiosignal to be diagnosed, and acquiring a second diagnosis tag corresponding to the historical electrocardiosignal and a corresponding similarity; generating an electrocardio diagnosis process prompt based on the electrocardio diagnosis process knowledge and a thinking chain technology; and taking each electrocardio feature, the first diagnosis tag, the diagnosis probability, the second diagnosis tag and the similarity as an electrocardio diagnosis context, and inputting the electrocardio diagnosis context, the electrocardio diagnosis knowledge and the electrocardio diagnosis process prompt into a preset large language model for diagnosis to obtain a diagnosis result output by the large language model. The purpose of improving the electrocardio diagnosis accuracy is achieved.

Disclosed herein includes a system for generating synthetic medical images from a text prompt and a system for using the synthetic medical images to train a computer-implemented system for diagnosing a disease, generating a report, or self-improving. Exemplary methods include training a system for generating a synthetic medical image, generating a synthetic image that is accurate based off the evaluation of clinicians, generating synthetic images of atypical cases, improving systems for diagnosing a disease using synthetic medical images, improving systems for diagnosing a genetic mutation using synthetic medical images, and improving systems for generating reports from medical images. Further described are devices and systems for implementing such methods.

The invention relates to an image recognition and expert system fused wheat disease intelligent diagnosis system and method, and belongs to the technical field of wheat disease diagnosis. Different processing modes are adopted for different detection results; for the condition that the disease image features are detected and the corresponding disease is unique, the disease result is directly output; a second expert system module performs further identification on the condition that the detected disease image features are not unique corresponding to the disease; and for the condition that no disease image feature is detected, the first expert system module performs diagnosis, if the disease type is diagnosed, a disease result is output, and if the disease type is not diagnosed, the manual judgment module can perform further diagnosis. According to the system and the method, all types of scenes such as obvious image features, similar image features, non-image feature dominant and unknown diseases can be covered, and intelligent diagnosis of various types of wheat diseases is realized.

According to an embodiment of the present disclosure, disclosed is a method for evaluating qualities of electrocardiogram data and diagnosing a disease only with a signal having an excellent quality. Specifically, according to the present disclosure, a computing device evaluates qualities of electrocardiogram data obtained from a plurality of leads, excludes electrocardiogram data obtained from at least one lead among the plurality of leads based on the evaluation of the qualities of the electrocardiogram data, and performs electrocardiogram analysis based on remaining electrocardiogram data by using a pre-learned electrocardiogram analysis model.

Methods and systems are disclosed for using medical imaging data to diagnose peripheral arterial disease. In a method, a plurality of artificial intelligence based neural network models are trained on medical imaging data of a large population of anonymous patients after labeling and structuring the data for training and testing purposes. Medical imaging data of a known patient is then processed by the plurality of pre-trained artificial intelligence based neural network models to diagnose peripheral arterial disease. A rule-based algorithm integrates the predictions made by the pre-trained neural network models. An inference engine analyzes the integrated predictions data for the known patient, detects any anomalies in the pixel intensities present in each medical image, and performs volumetric calculations. A report generation engine generates medical reports for the known patient. A visualization tool enables a clinician to display and view the results of the diagnoses superimposed on medical images.

System and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular

The disclosure provides methods for detecting and diagnosing diseases and conditions associated with defects in cardiolipin remodeling. In some embodiments, the present technology relates to methods for detecting the presence or amount of cardiolipin isoforms and / or the presence or amount of enzymes involved in cardiolipin remodeling.

The disclosure provides apparatus and methods related to the assessment of the fragility and / or deformability of cells, comprising applying negative pressure to an interior volume defined by a hollow member that comprises a fenestration, wherein the negative pressure is sufficient to(1 ) partially aspirate a cell into the interior volume of the hollow member through the fenestration at a time to, and (2) following to, rupture the cell at a time tr, resulting in the complete aspiration of the cell into the interior volume of the hollow member, and measuring a time to rupture of the cell (T) between tr and to. The apparatus and methods provided herein use small sample volumes and provide improved sensitivity and reproducibility over existing methods of assessing cell fragility and / or deformability. The apparatus and methods provided herein are useful for, e.g., evaluating the quality of stored blood to facilitate decisions regarding transfusion and diagnosing a disease, disorder, or condition.

The invention encompasses a real time, point of care, diagnostic system, including a lateral flow test cassette, a data reader, and an application for processing test results and methods of diagnosis of a disease or virus.

A method of isolating ultrashort single-stranded cell-free DNA (uscfDNA) is described as well as methods of using the uscfDNA for detecting biomarkers and diagnosing diseases and disorders.

The present invention relates to a disease-specific biomarker for early prediction and diagnosis of preeclampsia and use thereof, and a composition for prediction or diagnosis of preeclampsia according to an aspect or a method of providing information for prediction or diagnosis thereof, can simply and effectively predict or diagnose the disease by measuring and comparing the mRNA level of a disease-specific protein or a gene encoding the protein changed in a patient.

An infection status of a subject is determined using sequence reads from a biological sample of the subject. For each respective alternative splicing (AS) event in a plurality of AS events, there is determined (i) a corresponding first abundance metric of the AS event in the biological sample based on a mapping of each sequence read to one or more reference splice junctions in a plurality of reference splice junctions, and (ii) a corresponding second abundance metric of the AS event in the biological sample based on a mapping of each respective sequence read of the plurality of sequence reads to one or more reference isoforms in a plurality of reference isoforms. Each AS event corresponds to a locus in a reference genome. The first and second abundance metrics for each AS event are inputted into a model to obtain a predicted infection status of the subject as model output.

The disclosure herein relates to the development and production of novel antibodies and antigen-binding fragments thereof that bind to TL1A and are useful in the treatment, prevention, and diagnosis of diseases, disorders, or inflammation, including, for example, autoimmune diseases, including rheumatoid arthritis, inflammatory bowel disease, atopic dermatitis, systemic lupus erythematosus, asthma, ulcerative colitis, Crohn's disease, psoriasis, primary biliary cirrhosis, primary biliary cholangitis, ankylosing spondylitis, and fibrosis, including intestinal fibrosis, pulmonary fibrosis, and liver fibrosis. Some of the elements of the final antibody structure are designed de novo by a computer system and its data training set, without reference to a particular reference molecule.