62 results about "Acquired diseases" patented technology

The present invention discloses a medical big data based disease automatic assistance diagnosis system and method. The system comprises: a background data storage unit; an information processing unit, which specifically comprises: a statistical classification module, used for acquiring case data in the background data storage unit, and performing statistical classification on the case data, so as to obtain a symptom set and a definitively diagnosed disease type set; a diagnosed disease set calculation module, used for calculating a definitively diagnosed symptom set of various diseases according to the symptom set and the disease type set that are obtained by the statistical classification module; and a disease automatic diagnosis module, used for acquiring disease symptom data provided by a user, generating a selection symptom set, comparing the selection symptom set with the definitively diagnosed symptom set of various diseases and performing calculation, so as to obtain a disease determination result; and a man-machine interaction unit, used for displaying an interface of selecting a disease by the user, and outputting a disease diagnosis result. The method disclosed by the present invention is simple, easy and strong in operatability, and provides a new clinic assistant diagnosis tool for the medical field, and reduces an error/miss diagnosis rate.

The present invention provides polynucleotides and expression vectors containing a sequence encoding a soluble lysosomal enzyme and a sequence encoding Tat protein transduction domain (PTD), and the corresponding polypeptides. The present demonstrates the utility of these protein fusions in altering the bioavailability of proteins for use in treating genetic diseases or acquired diseases. The invention further provides cell expression systems, and methods of treating a genetic disease or cancer in a mammal using the polynucleotides, polypeptides, or expression system of the present invention.

The invention discloses a disease risk predicting method, a device and a computer storage medium, wherein the disease risk predicting method, the device and the computer storage medium relate to the field of data analysis technology. More comprehensive analysis can be performed on the disease data for improving disease risk predicting precision. The disease risk predicting method comprises the steps of acquiring disease sample data with relevance, wherein the disease sample data comprises the disease data of each disease type and disease related data, and furthermore each disease type label isrecorded in the disease sample data; inputting the disease sample data with relevance into a deep learning model for training, constructing a disease risk predicting model which is used for predicting the risk predicting result of the disease data in each disease type; and when to-be-predicted disease data are received, based on the disease risk predicting model, outputting the risk predicting result of the to-be-predicted disease data in each disease type.

The present invention relates to the discovery of an effective treatment for a variety of gain-of-function diseases, in particular, Huntington's disease (HD). The present invention utilizes RNA Interference technology (RNAi) against polymorphic regions in the genes encoding various gain-of-function mutant proteins resulting in an effective treatment for the gain-of-function disease.

The invention relates to agricultural engineering and particularly relates to a method and a system for acquiring the disease severity of a leaf under an open field environment. The method comprises the following steps: taking a picture of a leaf against a black flat plate; extracting edge features in a gray image of the picture to divide the image into a plurality of regions; finding out leaf regions and diseased spot regions from the regions according to color features in a color image of the picture; and judging the disease severity of the leaf according to the number of the diseased spot regions and the area ratio of the diseased spot regions to the leaf regions. The disease severity of a leaf can be accurately calculated under an open field environment.

The invention relates to a road maintenance processing method. The method comprises the steps that a patrol task instruction sent by a first terminal is received, wherein the patrol task instruction comprises a patrol road mark marked in a three-dimensional geographic information system, a patrol process marked in a building information model BIM and a road component mark set; the patrol task instruction is sent to a second terminal, so that the second terminal carries out patrolling according to the patrol task instruction to acquire disease comprehensive information; the disease comprehensive information sent by the second terminal is received; according to the disease comprehensive information, the BIM information corresponding to a target road component is acquired; and disease analyzing is carried out according to the BIM information corresponding to the disease comprehensive information and the target road component, so as to acquire a corresponding disease maintenance plan. In addition, the invention further provided a road maintenance processing device and system. According to the road maintenance processing method, the device and the system, the three-dimensional geographic information system and the road BIM are combined to improve the scientific degree of the whole road maintenance process, and the road maintenance processing efficiency is improved.

The invention discloses a tumor patient follow-up feedback pushing method and system. The method includes: acquiring disease information of a patient; matching corresponding follow-up scheme data information in a pre-stored tumor follow-up scheme library according to the disease information, and generating a follow-up feedback request containing the follow-up scheme data information according to the follow-up scheme data information; sending the follow-up feedback request to a patient end; and receiving the follow-up feedback request fed from the patient end, and acquiring a follow-up record. The method acquires the disease information of the patient, matches the follow-up scheme data information according to the pre-stored disease information, actively sends the follow-up feedback request to a patient end, and receives the follow-up feedback request fed from the patient end; a doctor analyzes the condition of the patient according to the follow-up record and send an alarm notification, the patient can effectively and timely receives the professional alarm notification and receives a treatment at optimal time, and aggravation of the condition of the patient due to late treatment can be avoided.

The invention discloses a department registration guiding method and terminal equipment and relates to the field of hospital navigation technology. The method comprises the steps that sign data of a user is acquired; a mentioned keyword is extracted from the sign data; disease symptom records corresponding to the mentioned keyword are acquired according to a pre-stored disease symptom data table; similarities between the sign data and the acquired disease symptom records are determined according to the mentioned keyword; a target disease symptom record is extracted from the acquired disease symptom records according to the determined similarities; and the department of a disease is determined according to the target disease symptom record, and department registration guidance is generated according to the department. By the adoption of the scheme, the number of times of wrong registration of a patient can be reduced, doctor seeing time is saved for the patient, and convenience is provided for the patient to see a doctor.

The embodiment of the invention provides a disease diagnosis method and a terminal, wherein the method comprises the following steps: acquiring disease symptoms of a user; judging the disease category of the user according to the disease symptoms of the user and pre-stored disease sample data, acquiring a rehabilitation proposal corresponding to the disease category, wherein the disease sample data comprise disease names, disease symptoms and rehabilitation proposals for various diseases; outputting the disease category and the rehabilitation proposal to the user. The terminal is used to judge the disease category of the user according to the symptoms of the user, and provides the corresponding rehabilitation proposal for the user.

The invention discloses a NiTi memory alloy gradient porous personalized dental implant and a manufacturing method thereof. The method comprises the following steps: carrying out grid adjustment and curved surface fitting on acquired diseased tooth data, so as to obtain a relatively smooth diseased tooth model; and separating a dental crown part from a dental root part by virtue of a cut plane, and designing a base station at the top of the dental root of the dental implant according to a required retention force, wherein gradient porous structures are distributed at the dental root part, thedental root is manufactured from NiTi memory alloy with a memory effect through 3D printing and has the memory effect after being trained. The dental root generates phase change at a body temperaturephase-transition temperature point and is deformed, the base station at the dental root and an implanted part at the bottom of the dental root have self-swelling effects, so that a gum is automatically filled with the dental root, and the dental root has a pre-tightening force. BBC porous structures and negative poisson ratio porous structures are distributed at the dental implant and can generatetransverse deformation deference during the phase change, and the discontinuous deformation is generated at the bottom of a dental implant body so as to form a thread-similar structure, so that the contact area is increased, a fixation effect is achieved, and the dental implant is unlikely to be loosened.

The present invention discloses a human body part-based hospital guide method, client and server. According to embodiments of the present invention, a client acquires a human body part input by a user, and sends a disease match request to a server according to the human body part; the client receives and displays disease information matched by the server for user's selection; the client acquires disease information selected by the user, and send a department match request to the server; the server receives and displays department information matched by the server for user's selection; the client acquires department information selected by the user, and sends a doctor match request to the server according to the department information; and the client receives and displays doctor resources matched by the server for user's hospital guidance. The client according to the present invention, based on a human body part directly relevant to a disease, interacts with a user multiple times, sends information closest to user's demands to the server to request matching, and accurately acquires doctor resources desired by the user, thereby improving hospital guide efficiency.

The invention provides a miRNA-based disease relation analysis method and device. The method includes: constructing miRNA functional information according to miRNA expression of patients with a targetdisease and a normal control group; acquiring disease class information; calculating between-class distance between the miRNA functional information and the disease class information; constructing acomposite network according to the between-class distance, and generating disease relation information corresponding to the target disease. The method is detailed and accurate in analysis result and high in applicability, can be applied to molecular complex disease complication prediction analysis related theoretical researches and various clinical complex disease recovery assessment and has important significance to analysis in biology and medical science related fields.

The present invention discloses a method for attaining potato plates which are disease resistant by utilizing agrobacterium-mediated hrap gene. After the combined inoculation of the method and the bacteria allergic protein harpinPss, the allergic reaction caused by harpinPss can be promoted in the intercellular space of all inoculated plates, and the polymeride of harpinPss is dissociated, so the disease resisting effect is better, and the disease resistance of the potato plates can be promoted. The hrap gene is introduced in the potato plates through the agrobacterium-mediated, thus resulting that the potato plates have the ability to resist the late blight and the bacterial wilt. The present invention has the technical proposal that the pre-cultured explants are inoculated in the agrobacterium germ liquid to be soaked, explants after being soaked select the tube seedling which can root after two times of root selections by co-culturing, callus of induce, bud inducting and rootage cultivating and selecting, and the potted transformed plants are transferred after the mass propagation, the transformed plants select positive plants by the methods of the PCR detection and the Southern hybridization detection, and then the potato plates which are disease resistant can be obtained by the in-vivo inoculation resistance identification. The present invention improves the callus of inducing and the bud inducing of the explants, and enhances the agrobacterium-mediated ability. That the roots of the explants are selected by two times can eliminate the false positive plates in the transformation process , avoid the continuing cultivation to the false positive plates, save the labour force and decrease the manufacturing cost.

The invention discloses a disease-associated gene combination counting method and system. The method comprises computing the significance of every mononucleotide polymorphic site in a gene sequence through a genome-wide association analysis method, wherein the significance presents the degree of association between the mononucleotide polymorphic site and diseases, acquiring the significance of themononucleotide polymorphic sites; according to the significance and a threshold value, screening out the mononucleotide polymorphic sites associated with the diseases to acquire the associated mononucleotide polymorphic sites; through an extreme gradient-based Boosting ensemble learning method, categorizing people corresponding to the associated mononucleotide polymorphic sites into affected onesand non-affected ones and further acquiring associated gene combinations. By combining the genome-wide association analysis method and the gradient-based Boosting ensemble learning method to categorize people corresponding to the associated mononucleotide polymorphic sites into the affected ones and the non-affected ones and further to acquire the associated gene combinations, the disease-associated gene combination counting method can improve the accuracy of acquired disease-associated gene combination results.

The invention discloses an intelligent evaluation and diagnosis method and a system for heart disease types and severity degrees. The method comprises the steps of acquiring disease characteristic data and demographic characteristic data, and analyzing the acquired ultrasonic echocardiogram report data and the patient demographic characteristic data by utilizing a learning model to obtain a modelevaluation index, a heart disease type and a heart disease severity. According to the invention, a data mining method is adopted, so that data preprocessing, data screening and other operations are carried out on data through the data mining correlation method. The method is adopted for selecting a noise ratio during the characteristics selection process. A random forest model is adopted for carrying out the classification prediction of the heart disease severity. Meanwhile, an effective research method is obtained through comparing and analyzing the algorithm performances and the learning effects of the random forest model, a naive Bayes classifier, a decision tree model and a BP neural network model. Moreover, a standard for the severity classification of heart disease patients and a prediction method for predicting the treatment risk of the heart disease operation are provided.

The invention discloses a drug recommendation method, an electronic device and a storage medium. The method comprises the following steps: acquiring a disease set; acquiring disease association data according to the disease set; acquiring disease matching data of each drug; calculating a drug matching coefficient of each drug according to the disease association data and the disease matching dataof each drug; recommending drugs whose matching coefficients meet recommending conditions. Based on the correlation coefficients between different diseases and the disease matching coefficients between specific drugs and various diseases, the drug matching coefficients between the drugs and the disease set input by a demander are comprehensively evaluated, the link between the diseases is taken into account, the effect of the drugs on various diseases is also considered, and recommending results are more accurate. Moreover, the disease association data and the disease matching data of the drugs can pool wisdom and are scientific and transparent, and new drug data can be conveniently populated.

The present invention relates to the discovery of an effective treatment for a variety of gain-of-function diseases, in particular, Huntington's disease (HD). The present invention utilizes RNA Interference technology (RNAi) against polymorphic regions in the genes encoding various gain-of-function mutant proteins resulting in an effective treatment for the gain-of-function disease.

A disease information acquisition unit acquires disease information of a patient and information of a disease period of the disease information, a display period designation receiving unit receives a designation of information of a display period for which medical data is displayed, and a display control unit displays a list of the disease information in which at least a part of the disease period is included in the display period and that acquires medical data of the medical treatment items, which are associated with at least one selected piece of disease information in the list of the disease information, and displays the acquired medical data in time series. In a case in which the display period has been changed, the display control unit displays a changed list of disease information in which at least a part of the disease period is included in a display period after the change.

The embodiment of the invention provides a method for processing colorectal cancer medical data, a device for processing colorectal cancer medical data, a computer readable medium and electronic equipment. The method for processing colorectal cancer medical data comprises the following steps of: determining a recommended treatment scheme for the colorectal cancer of the current patient according to the acquired disease condition parameters of the colorectal cancer of the current patient and medical experience; according to the disease condition parameters of the colorectal cancer, matching inthe medical record information of a historical patient to determine target medical record information; and taking the recommended treatment scheme and the target medical record information as medicaldecision information of the colorectal cancer corresponding to the current patient. According to the technical scheme of the embodiment of the invention, the medical decision information of the colorectal cancer corresponding to the current patient is determined, and the factors of medical experience and clinical medical record are considered at the same time, so that the management of medical data and the practicability of analysis results based on medical data are improved, so that the acquired medical decision information for the colorectal cancer can meet the requirement of clinical use.

The invention discloses a novel physical examination report generation method, which comprises the following steps of: acquiring first identity information of a patient and searching physical examination data information corresponding to the first identity information through a medical database, wherein the physical examination data information comprises doctor comments and multiple pieces of physical examination item data, carrying out word decomposition on the doctor comments through a word segmentation technology to obtain a plurality of chunks, identifying the plurality of chunks to extract chunks containing physical examination item terms in the plurality of chunks, and carrying out index marking, performing statistics on the plurality of pieces of physical examination item data through a statistical algorithm to extract examination data, and acquiring disease names corresponding to the examination data through a disease lexicon, calculating the disease name text through a vectoralgorithm to obtain a name vector, and associating the name vector with the chunk subjected to index marking to generate an item label corresponding to the disease name, and storing the physical examination report generated by the item label in the medical database corresponding to the first identity information.

The invention provides a diabetic foot knowledge graph generation method and device and a readable storage medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring disease corpus data of related fields of the diabetic foot; extracting a plurality of disease entities from the disease corpus data; obtaining attribute information of each disease entity, wherein the attribute information is used for representing feature information of each disease entity; utilizing the attribute information to construct an association relationship among a plurality of disease entities; creating a knowledge base of the diabetic foot based on the association relationship; and associating the knowledge base of the diabetic foot with a pre-created knowledgegraph architecture to generate a knowledge graph of the diabetic foot. According to the scheme, the knowledge graph is generated by constructing the knowledge base of the diabetic foot and then associating the knowledge base with the pre-created knowledge graph architecture, so that the knowledge graph can be constructed directly based on the knowledge graph architecture when the knowledge graphof the diabetic foot is constructed, and the knowledge graph can be constructed more quickly and conveniently.

The invention discloses a medical self-diagnosis service design method based on credible combination assessment under big data. The method comprises the following steps of analyzing an application mode corresponding to a basic self-diagnosis service and a big data processing flow related to a process of building a disease self-diagnosis service; decomposing a big data processing task into a set of functionally-independent sub-tasks, and forming a task planning scheme of building the disease self-diagnosis service; using a credible combination assessment method to select a cloud service combination scheme with the optimal QoS for the disease self-diagnosis service based on the requirement of each sub-task on computing resources and storage resources in the task planning scheme; and achieving a big data analysis algorithm of the disease self-diagnosis service in the cloud service corresponding to each sub-task, thus completing deployment and execution of the disease self-diagnosis service. According to the method provided by the invention, the big data about electronic medical records acquired by searching is stored, and subjected to online retrieval and processing and analysis, so that the user can call the disease self-diagnosis service on line to acquire disease self-diagnosis help.

The invention provides a parameter determination method and setting method of an implantable medical device (IMD) of a human body and equipment. The parameter determination method comprises: acquiring disease symptom characteristic information of a user; searching for pre-stored disease symptom characteristic information conforming to the disease symptom characteristic information, wherein the pre-stored disease symptom characteristic information is associated with at least one set of operating parameters; and determining recommended operating parameters according to the pre-stored disease symptom characteristic information and the associated operating parameters thereof. According to the technical solution provided by the invention, the operating parameters of the implantable medical device of the human body are set without the need for an artificial doctor intervention setting process, errors caused by human experience are avoided, going to a designated place by the user for setting is not needed, the purpose of automatically setting the operating parameters can be realized through a remote communication manner, and the efficiency is higher.