334 results about "Diseases types" patented technology

Disclosed herein are systems, methods, and devices for classifying ophthalmic images according to disease type, state, and stage. The disclosed invention details systems, methods, and devices to perform the aforementioned classification based on weighted-linkage of an ensemble of machine learning models. In some parts, each model is trained on a training data set and tested on a test dataset. In other parts, the models are ranked based on classification performance, and model weights are assigned based on model rank. To classify an ophthalmic image, that image is presented to each model of the ensemble for classification, yielding a probabilistic classification score—of each model. Using the model weights, a weighted-average of the individual model-generated probabilistic scores is computed and used for the classification.

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

This disclosure discloses various technical features for creating robotic humanoid movements, actions, and interactions with tools and the instrumented environment by automatically building movements for the humanoid; actions and behaviors of the humanoid based on a set of computer-encoded robotic movement and action primitives. The primitives are defined by motions/actions of articulated degrees of freedom that range in complexity from simple to complex, and which can be combined in any form in serial/parallel fashion. These motion-primitives are termed to be minimanipulations and each has a clear time-indexed command input-structure and output behavior/performance profile that is intended to achieve a certain function. Minimanipulations comprise a new way of creating a programmable-by-example platform for robots. The minimanipulation electronic libraries provide a large suite of higher-level sensing-and-execution sequences that are common building blocks for complex tasks, such as cooking, taking care of the infirm, or other tasks performed by robots.

Compositions, methods and kits are described for identifying biomolecules (e.g., proteins and nucleic acids) expressed in a biological sample that are associated with the presence, development, or progression of a disease (such as cancer), or more generally determination of the etiology or risk factors associated with a disease. Sample types analyzed by the disclosed methods include but are not limited to archival tissue blocks that have been preserved in a fixative, tissue biopsy samples, tissue microarrays, and so forth. The methods disclosed herein correlate expression profiles of biomolecules with various disease types, and allow for the determination of relative survival rates; in some embodiments, the methods permit determination of survival rates for a subject with cancer. In other embodiments, the disclosure relates to methods for evaluating therapeutic regimes for the treatment, such as treatment of cancer.

The invention provides an intelligent health management system based on an elder-caring robot; the system comprises an elder-caring robot, a remote terminal and a cloud server; the elder-caring robot comprises a reminder and a detector mutually connected; the reminder starts path planning and mobile functions according to a preset medical solution, searches the elder according to a face recognition technology and a sound source positioning technology, communicates with the elder through a voice interaction technology, and broadcasts prompt contents; the detector monitors an intelligent medicine box opening state on the elder-caring robot, detects the elder complete conditions on the prompt contents through the image identification technology and the voice interaction technology, and synchronizes the detection result onto the cloud server; the cloud server sends the information to the remote terminal, thus returning feedbacks to children or medical personnel. The intelligent health management system can provide complete, professional, intelligent and safe one-stop intelligent health management services, so children can remotely monitor, track and detect elder living conditions in a long term, thus realizing disease types and risk predictions.

A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.

The invention provides a construction method and application of a thoracic disease detection model. The construction method comprises the following steps: A, acquiring chest X-ray images of a specified number of thoracic disease patients; B, performing image preprocessing on the X-ray images to obtain pre-processed image data; and C, inputting the pre-processed image data to a convolution neural network model for training to obtain the trained model for thoracic disease detection. The thoracic disease detection model can accurately predict a type and a location of a thoracic disease, the diagnosis time of the doctor is greatly shortened, and the rate of missed diagnosis and misdiagnosis is lowered.

The method includes: receiving the patient's condition information, the condition information includes the specified disease type of the patient; using the patient's condition information as a parameter, generating a follow-up request, and the follow-up request includes expected patient feedback information related to disease treatment; Sending the follow-up request to the patient terminal through the network; receiving the follow-up response to the follow-up request fed back by the patient terminal; storing the information contained in the follow-up response. The present invention can effectively overcome the problem in the prior art of sending highly targeted follow-up information to patients conveniently and efficiently.

The invention discloses a follow-up method and a system thereof. The method includes: acquiring related information of a patient before leaving a hospital; managing medical records, wherein a corresponding follow-up template is invoked from a database according to the related information of the patient, and follow-up contents with corresponding items are generated; executing medical-record management steps, and recording a follow-up result corresponding to the patient; and analyzing records of the follow-up result of the patient according to a predetermined analysis method. According to the method, a disease type to which the patient belongs can be automatically determined, the customized follow-up template of a doctor which is responsible for the disease type can be imported, and a preliminary follow-up plan can be automatically generated. The post-hospital follow-up records are combined to obtain medical big data, which are individually for both the doctor and the patient, by integration, follow-up quality and effects are effectively improved, and data counting and management are facilitated.

The invention relates to a dressing aid which is intended for the infirm or persons with reduced motor skills. The inventive aid is of the type which facilitates said persons in pulling an item of clothing (5) onto the lower limbs of the body. The aid, which consists of at least one flexible strap (1) having a clamp piece (2) disposed at one of the ends thereof, comprises means of gripping the clothing to be worn and means of positioning said clothing (5) on the desired parts of the body. Said aid consists of two flexible straps (1), each of said straps comprising a clamp piece (2) at one of the ends thereof and a grip means (8) at the other end of same. Moreover, said straps are connected transversely at the central part thereof by means of a centre strap (3).

The invention provides a method for preparing a flexible electrode, wherein titanium dioxide nanorod arrays grow on a surface of a carbon fabric regarded as a substrate. The method comprises the following steps of: (1) putting the carbon fabric in a solution formed by mixing butyl titanate, hydrochloric acid and water, wherein the percent by volume of the butyl titanate is 4%-5%, the percent by volume of the hydrochloric acid is 41%-52%, and the balance is water; and (2) heating the carbon fabric contained mixed solution at a temperature of 170-200 DEG C for 40-60 minutes by adopting microwaves to obtain a titanium dioxide nanocrystalline electrode. Prior to the step (1), the method further comprises a cleaning step, in which the carbon fabric is subjected to ultrasonic processing for 30-60 minutes by respectively using acetone, water and ethanol. The method effectively solves the problems of infirm bonding between titanium dioxide granules and the substrate, and disordered growing in the conventional photoanode preparing process; for the first time, the titanium dioxide nanorod arrays evenly and firmly grow on the surface of the carbon fabric, and are synthesized once only; and the method is simple, has low cost for the reacting raw materials, is efficient and fast, thereby being favorable for popularization.

The invention provides a disease self-diagnosing method for completing data training based on user feedback information. The method includes the following steps that a disease self-diagnosing data model is established and includes disease data, disease type data, symptom data and disease-symptom associated data; a user obtains a self-diagnosing result and a suggestion for treatment seeking through the disease self-diagnosing data model according to own symptoms; the user gives feedback according to the self-diagnosing result or the result of treatment seeking; the disease self-diagnosing data model performs analysis and learning according to the feedback to constantly perform data training. The method has the advantages that through the method, the disease self-diagnosing data model is established, the method for completing data training based on the user feedback information is established for providing a perfect data training path and method for disease self-diagnosing information, and more scientific and accurate bases are provided for self-diagnosing of the patient.

The invention provides a control method and a control device for realizing disease prediction based on an eigenvector. The control method comprises the steps of: a, converting one or more original vectorized representations into a dense vectorized representation based on an Embedding model; b, regarding the dense vectorized representation as an input based on a diagnostic model, and determining the similarity of each disease of the dense vectorized representation in the diagnostic model; c, and determining a disease type with the highest matching degree with the dense vectorized representationbased on the similarity of each disease of the dense vectorized representation in the diagnostic model. The control method and the control device integrate one or more pieces of case information of auser, takes a super-long vector representing a panoramic disease of the patient, reserve a relevance hypothesis, introduce a deep neural network model to learn an interactive feature of a single feature and depth in the super-long vector, and determine a probability of each disease matched with the user case information. The control method and the control device have the advantages of simple operation, convenient use and high commercial value.

The invention relates to a method for detecting chromosome microdeletion and micro-duplication of a human embryo. The method comprises the following steps of performing whole genome amplification on cells cultured in vitro, interrupting DNA (deoxyribonucleic acid) molecules, and sequencing DNA fragments to obtain sequencing reads; comparing the sequencing reads with a reference sequence, and positioning the sequencing reads on the reference sequence; screening non-repeated areas of the reference sequence, and reserving the non-repeated areas; establishing a matrix of read number in windows through normal samples, analyzing the data of the normal samples, performing statistics on the read number of all the windows in the non-repeated areas, and establishing a probability matrix of the read number and chromosome enpeoids; calculating the copy number, i.e., the A/B/C state, of loci; selecting m continuous loci, i.e., the A state, as micro-duplication loci, and selecting m continuous loci, i.e., the C state, as microdeletion loci; contrasting the micro-duplication loci and the microdeletion loci with the existing CNV (copy number variation) and disease database, performing basic gene annotation and gene function analysis which relates to deletion parts, and annotating with a microdeletion syndrome disease type.

The invention discloses a method and a system for processing inquiry information, and belongs to the field of information processing. The method includes displaying pictures for a user to select physically uncomfortable parts; acquiring symptom information corresponding to selected uncomfortable parts from a preliminarily stored identification symptom list according to the physically uncomfortable parts selected by the user on the pictures and displaying the symptom information on the pictures; receiving symptoms which are selected by the user from the displayed symptom information, acquiring and displaying enquiry questions for the user according to the selected symptoms; receiving reply information which is submitted by the user according to the displayed enquiry questions; acquiring weights corresponding to the reply information from a preliminarily stored disease measurement table according to the reply information; determining inquiry disease types of the user according to the sum of the weights corresponding to the different pieces of reply information. The method and the system have the advantages that the inquiry information of the user can be automatically processed by the aid of a computer and an internet, so that the user can be effectively assisted to conveniently and accurately see a doctor to effectively treat diseases.

The invention provides an image report system. The image report system comprises a report inputting module, a report generating module, an editing module, an inquiring module and a displaying module; the report inputting module is used for inputting a disease type and a diagnosis result of a patient according to basic information of the patient; the report generating module is used for calling a corresponding template in a database according to the disease type of the patient and generating a diagnosis report of the patient according to the personal information and the diagnosis result of the patient; the editing module is used for editing the diagnosis report generated by the report generating module according to opinions of doctors with the permission level from high to low; the inquiring module is used for calling an image report associated with inquiring information in the database according to the inquiring information input by an operator, wherein the image report comprises the diagnosis report and image data; the displaying module is used for displaying the diagnosis report and the image data which are called by the inquiring module in the database and dynamically displaying the image data. According to the image report system, module refinement is achieved, the diagnosis report is automatically generated according to the diagnosis opinions of the doctors, therefore, the diagnosis level of the doctors is increased, and the image report displaying level is increased.

A quantification of the expression levels of a number of specific genes and their corresponding proteins can be utilized in accurately determining, using samples from faeces or blood, whether the patient is suffering from irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD), and in a follow up analysis using a biopsy, determine if the same patient is afflicted with ulcerative colitis (UC) or Crohn's disease (CD). The method also has utility in determining the severity of the disease, as well as observing a patient's response to treatment.

The invention discloses an intelligent underwriting processing method, server and storage medium. The intelligent underwriting processing method receives the insurance application information of an insured person sent by a user terminal, and judges whether an abnormal health notification item in the insurance application information is selected or not. When the abnormal health notification item isselected, extracting a disease questionnaire corresponding to the disease type from a questionnaire database according to the selected disease type in the abnormal health notification item and feeding back the disease questionnaire to a user terminal; Receiving a disease questionnaire fed back by a user terminal, and calculating an insurance risk value according to an answer weight of a questionshown in the disease questionnaire and an option score of a selected option; When the insured risk value of the policyholder is less than the preset first risk threshold, the notification informationof the underwriting is fed back to the user terminal. Automatic issuance of underwriting conclusions is presented based on the answers submitted by the applicant without manual processing, so that theworkload of underwriters is reduced and the period of underwriting review is shortened.

The invention discloses a computing method and a computing method system for crop disease index. The computing method comprises the following steps: acquiring image of crop and pre-processing the image; dividing the pre-processed image into multiple sub-images and extracting color characters of the sub-images; using a minimum distance classifier for identifying the disease types and disease level of the sub-images according to the color characters of the sub-images; computing the crop disease index according to the disease types and disease level of the sub-images. The method solves that the disease index computing of the prior art depends on experience and knowledge of pathology of field crop protection persons, the statistical result is inaccurate and manual computation is required. The method is conducive to improve the prevention and treatment level for crop disease index and promote the implementation of precision agriculture, and novel method and technology are provided for the crop disease prevention and treatment field.

The invention provides a bridge maintenance disease recording, identifying and processing measure guiding method and system. The method comprises: collecting a large number of bridge disease conditions before the management of an inspection task, carrying out the classification of the disease conditions into a corresponding disease library, and providing a corresponding treatment measure for eachdisease, building a treatment measure library, and enabling the diseases and the treatment methods to correspond to each other; performing theme label management on each disease and setting differentweights; and determining the disease type according to the tag weight, and providing complete processing scheme guidance according to an associated processing method. Maintenance inspectors record inspection paths through a mobile terminal GPS, when bridge part diseases are found, structural information of a bridge can be obtained by scanning preset two-dimensional codes on the structure, photographing and disease information filling and reporting are conducted on the disease parts at the same time, and the system can classify the diseases according to disease labels and recommend corresponding treatment methods. Automatic classification and identification of diseases can be realized, treatment measure guidance is provided, and the method is simple and convenient.

The invention relates to a recombinant vaccine strain for foot-and-mouth disease type A, which is constructed by a gene recombination technology and featured with high valence, high antigen compatibility and high immune protective rate, as well as a preparation method thereof and an application thereof. An antigen nucleotide sequence of the vaccine strain is shown by SEQ ID NO. 1; a rescuing system is an efficient eukaryotic plasmid, which is manually constructed and can express an accurate foot-and-mouth disease virus genome RNA; therefore, a foot-and-mouth disease recombinant virus can be constructed and prepared; through the adoption of the plasmid, the vaccine strain with high titer and good antigen compatibility can be prepared so as to prepare inactivated vaccines; after pigs and cattle are immunized, bodies can be effectively stimulated to generate immune responses and immune protective effects on the pig and cattle bodies can be provided; an A type AISA lineage of strain is challenged with 10000 times of 50% cattle infective dose (BID50), so that the immune protective rate reaches 100% and 50% protective dose (PD50) is 10.81-13.59; and the vaccine can be used for preventing and controlling foot-and-mouth diseases type A in China and neighboring countries.

The invention provides a maize leaf disease identification method, in particular to a maize leaf disease identification method based on a convolutional neural network model GoogleNet. The invention aims at solving the defects that the existing maize leaf disease identification technology is more in network model parameters and low in disease type identification accuracy. The maize leaf disease identification method comprises the following steps: 1, collecting a maize leaf image data set, expanding the collected maize leaf image data set, and then pre-processing image data set, wherein the pre-processed image data set is divided into a training set and a test set; 2, inputting the training set and the test set into the convolutional neural network model GoogleNet, and training and testing by using a first classifier so as to obtain an optimized convolutional neural network model GoogleNet; 3, inputting the test set into the optimized convolutional neural network model GoogleNet so as tocomplete the identification of types of maize leaf diseases. The maize leaf disease identification method is applied to the technical field of image identification.

The invention discloses a hyperspectral citrus leaf disease identification method based on a characteristic wavelength. According to the method, the characteristic wavelength is selected based on waveband operation by utilizing a hyperspectral technology to realize the discrimination and detection of various diseases of citrus leaves. By establishing a disease type discrimination model, a detection result of a disease type can be obtained only by acquiring a hyperspectral image of a to-be-detected sample for preprocessing and extracting a reflectivity data model under the corresponding characteristic wavelength, and the nondestructive, rapid and accurate identification of the citrus leaf disease type can be realized. The characteristic wavelength is selected by using the correlation coefficient of a waveband operation result and a mark value, the calculation is simple, and the judgment effect of the selected characteristic wavelength is good. After hyperspectral data of the to-be-detected sample is preprocessed, the spectral value of each pixel is substituted into the model, and the disease type and distribution can be visually displayed through colors, and the method is more intuitive.

The application discloses a method and system for tumor individualized clinical trial text mining. The method for the tumor individualized clinical trial text mining in the application includes the steps of (1) querying a preset clinical trial database according to to-be-tested object individualized information data, and screening clinical trial texts matching with the individualized information data; screening and obtaining the priority: disease type>gender>age>country>biomarker mutation information; (2) sorting the trial texts obtained from the screening in the step (1) into: gene mutation site complete matching>other gene mutation matching>gene matching>related gene matching; and (3) outputting the sorted trial texts, that is, individualized clinical trial texts. The method of the application can not only provide more and more accurate individualized treatment plans for the majority of patients and doctors; but also obtain more comprehensive, accurate and effective reference data, improve the accuracy and efficiency of individualized treatment plans, and save time and money.

The invention relates to big data, and provides an abnormal case identification method based on artificial intelligence which is applied to a platform server. The method comprises the steps: acquiringdiagnosis and treatment project data corresponding to the same disease, taking diagnosis and treatment time as a unit, and taking the diagnosis and treatment project data as words in a text to conduct text construction, wherein the constructed text comprises the diagnosis and treatment project data of different users of the same disease in the corresponding diagnosis and treatment time period; performing topic model construction on the text to obtain corresponding topic vector distribution, wherein each topic vector distribution is corresponding to one topic and comprises a plurality of wordidentifiers and corresponding word weights, and the topics have different user topic weights for different users; aligning the topic vector distribution corresponding to each text and performing clustering to obtain diagnosis and treatment item categories corresponding to each user at different time to form a diagnosis and treatment sequence corresponding to the user; and inputting the diagnosis and treatment sequence corresponding to each user at different diagnosis and treatment time into the process mining model to obtain a standard clinical path corresponding to the disease type so as to identify the abnormal case.

The invention relates to the technical field of data processing, in particular to a variable pesticide application method and system integrating remote sensing, a model and an algorithm, and the method comprises the steps: determining a mapping relation between geographic information of a growth site where crops are located and actual geographic information of the growth site; dividing the remotesensing image of the growing place where the crop is located into at least one grid according to the mapping relation, and enabling each grid to correspond to an operation area with a preset area in the growing place; and configuring a pesticide dosage matched with the potential disease type of the crop and the disease infection severity degree of the potential disease for the operation area of which the morbidity probability of the potential disease is greater than a preset value based on the predicted condition that the crop is infected with the potential disease for each operation area, soas to perform variable pesticide application on the crop in the growth site. The embodiment of the invention provides a variable pesticide application method and system integrating remote sensing, a model and an algorithm, and the method and system can control the dosage of pesticides, improve the utilization rate of the pesticides, and further improve the farmland yield.