151 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.

By producing the proper wave interference using superimposed angularly separate waves that overlap with the proper time-phase relationship (called “Time-Correlated Standing-wave Interference”), wave energy is amplified (by “Coherent Intensity Amplification”) and teleported to precise locations. For instance, in one application, energy is teleported to one or more areas within a living body for such therapeutic applications as destroying cancer cells or plaques within arteries. A system implementing this technique creates amplified constructive interference at one or more selected disease locations, while producing destructive interference at surrounding locations. In this application example, the technique allows energy to be “teleported” to tumor cells, plaques, or other diseased cells, for instance, to destroy them, while surrounding healthy cells receive virtually no energy, obviating collateral damage from the treatment. The same method can be used to diagnose disease by detecting energy teleported to different locations.

The present invention relates to a method, preferably a computer-implemented method, and to an apparatus for generating at least one intermediate cellular state of a cellular state evolution from an initial cellular state to a corresponding advanced cellular state. The present invention also relates to a computer program for generating at least one intermediate cellular state and to a non-transitory computer readable data medium storing the computer program. Moreover, the present invention relates to a method and to an apparatus for training a model for generating at least one intermediate cellular state of a cellular state evolution from an initial cellular state to a corresponding advanced cellular state. The present invention also relates to a computer program for training a model for generating at least one intermediate cellular state and to a non-transitory computer readable data medium storing the computer program. Furthermore, the present invention relates to a method for diagnosing a disease and forecasting patients' future clinical outcome making use of the method for generating at least one intermediate cellular state. Moreover, the present invention relates to an in-vitro method for transforming the identity of a cell.

The invention discloses a multi-modal enhanced representation collaborative learning pneumonia image recognition method, which comprises the following steps of: aiming at chest radiograph image data, respectively extracting visual modal features and text modal features, and generating rich feature representation fused with context semantics through a multi-modal feature coding strategy; a collaborative learning mechanism is adopted, complementarity of visual and text features is combined, the model is guided to carry out feature optimization and decision reasoning, and robustness and interpretability of the model are improved; in the classification reasoning stage, multi-modal auxiliary information is utilized to refine pathological region features, and fine-grained differences are effectively captured; and through an auxiliary information constraint mechanism, the recognition capability of the model on a tiny pathological mode is enhanced, and the pneumonia classification accuracy and generalization capability are improved. The method can be widely applied to computer vision tasks in the fields of medical image auxiliary diagnosis, disease detection and the like.

According to the ultrasonic imaging area array probe based on the array elements arranged in the regular hexagon mode and the imaging method, the array elements are arranged in the regular hexagon mode, each array element has the transmitting and receiving functions in three directions, and composite imaging with higher quality can be achieved in cooperation with unique addressing and signal processing algorithms. Therefore, the resolution ratio and the contrast ratio of an ultrasonic image are greatly improved, a doctor can see details of tissues and organs more clearly, diseases can be diagnosed more accurately, and the method has obvious advantages especially in the aspects of observation of minimal lesions, complex structures, blood flow signals and the like. The addressing technology provided by the invention can realize combined imaging of signals in multiple directions, so that the imaging angle is increased, the effective coverage range is expanded, and the imaging blind area is reduced. The method is particularly important in imaging of organs or lesions in complex shapes, information can be obtained more comprehensively, key details are prevented from being omitted, and a more complete image basis is provided for clinical diagnosis.

Disclosed is a sterile MRI probe infusion device for preparing and administering a hyperpolarized MRI probe to a patient in need thereof. The device includes one or more reaction chambers, where a hyperpolarized MRI probe is prepared, separated from the reaction mixture, concentrated, and a solution of suitable concentration for administration to a patient is prepared. Also disclosed is a method of preparing and administering a hyperpolarized MRI probe by the use of the device to a patient in need thereof for diagnosing stages of a disease or an adverse condition or monitoring progress of a treatment of the patient having a disease or an adverse condition.

Described herein are means for implementing annotation-efficient deep learning models utilizing sparsely-annotated or annotation-free training, in which trained models are then utilized for the processing of medical imaging. An exemplary system includes at least a processor and a memory to execute instructions for learning anatomical embeddings by forcing embeddings learned from multiple modalities; initiating a training sequence of an AI model by learning dense anatomical embeddings from unlabeled data, then deriving application-specific models to diagnose diseases with a small number of examples; executing collaborative learning to generate pretrained multimodal models; training the AI model using zero-shot or few-shot learning; embedding physiological and anatomical knowledge; embedding known physical principles refining the AI model; and outputting a trained AI model for use in diagnosing diseases and abnormal conditions in medical imaging. Other related embodiments are disclosed.

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 present application provides constructs comprising an antibody moiety that specifically binds to a mesothelin extracellular domain. Also provided are methods of making and using these constructs, and uses thereof, including treating and diagnosing diseases.

The present invention relates to a nucleic acid nanostructure comprising at least one scaffold chain and a plurality of staple chains wherein the nanostructure, preferably the at least one scaffold chain, comprises at least one nucleic acid sequence encoding a gene. The invention further relates to a composition comprising the nucleic acid nanostructure, and to a set of nucleic acid sequences or a set of plasmids encoding a nucleic acid nanostructure. Furthermore, the present invention relates to a nucleic acid nanostructure or a composition comprising a nucleic acid nanostructure for use in a medicament, preferably in a method for preventing, treating and / or diagnosing a disease or condition. The invention also relates to a method for expressing a gene from a nucleic acid nanostructure, and to the use of a nanostructure or composition for gene expression.

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.

The present invention relates to novel biomarkers and combinations thereof for cell type-specific and / or organ-specific extracellular vesicles, particularly brain-specific and / or neuron-specific extracellular vesicles. The present invention also relates to methods for the isolation and / or enrichment of cell type-specific and / or organ-specific extracellular vesicles, methods for the identification of extracellular vesicles derived from cells, and methods for diagnosing or prognosticating a disorder, such as a neurodegenerative disorder, using cell type-specific and / or organ-specific extracellular vesicles. Compositions in the form of kits of reagents for detecting cell type-specific and / or organ-specific extracellular vesicles are also provided.

A method of performing bisulfite sequencing on ultrashort single-stranded cell-free DNA (uscfDNA) and mononucleosomal cell-free DNA (mncfDNA) is described as well as methods of using the methylation profile of uscfDNA and / or mncfDNA for detecting biomarkers and diagnosing diseases and disorders.

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.

A method of automated diagnosis of disease database entities includes receiving a case processing request via an input application programming interface (API), extracting image data from the case processing request including at least one medical scan image of the patient, selecting at least a portion of the medical scan image(s) according to specified selection criteria, normalizing the selected at least a portion of the medical scan image(s), supplying the selected at least a portion of the medical scan image(s) to a machine learning model to generate a target medical condition prediction output, wherein the target medical condition prediction output is indicative of a likelihood that a patient will experience a future disease diagnosis event corresponding to the target medical condition, and automatically transmitting the target medical condition prediction output as an electronic transmission via an output API to a provider system associated with the patient.

The invention relates to the field of disease treatment, in particular to an anti-B7-H3 antibody or an antigen binding fragment thereof, a nucleic acid molecule encoding the antibody or the antigen binding fragment, and a method for preparing the antibody or the antigen binding fragment. The anti-B7-H3 antibody or the antigen binding fragment of the anti-B7-H3 antibody has high specificity and high affinity to B7-H3. The invention further relates to the use of said antibodies or antigen-binding fragments thereof in the treatment and diagnosis of disease.

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.

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

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.