33 results about "Drug-disease" patented technology

Given two heterogeneous entities, the prevalence of text data provides rich co-occurrence information for them. However, the co-occurrence only is noisy—not only may the co-occurrence just imply an accidental writing, but also it may just reflect the domain-specific common words. Only those strong relevance between entities supported by rich relevance contexts in data can indicate meaningful entity relationships. Strong relevance between heterogeneous entities are mined from their co-occurrences. Drug-disease therapeutic relationships are used as the example to demonstrate an application of this work.

An automated system for use by pharmacies, clinics or health care institutions which provides health information that comprises disease state information, the system having:

• • a) a clinic computer having access to medical information containing a medication profile for the patient, and
  • b) a remote computer having access to a drug-disease database

The disease state information being determined by a process where the clinic computer analyzes the medication information, creating a data packet comprising drug products being used, associating a unique identification number (UIDN) to the patient and data packet, and transmitting the UIDN and data packet to the remote computer. The remote computer then cross-referencing the drug products contained within said data packet with individual disease states and identifying disease state information that is relevant to be provided to a patient.

Disclosed is a network-based drug efficacy-assessing method, and an apparatus. The method comprises: computing a score for association between drugs and diseases by means of at least one of drug-adjacency-based inference, disease-adjacency-based inference, and module-distance-based inference; building a classifier for determining whether the drug is associated with the disease, using machine learning in which the score is employed as a feature; and determining the association between the drug and the disease by use of the classifier. The method and apparatus can search for drug-disease relation in which a drug can exert its pharmaceutical efficacy on a disease on the basis of a network constructed from protein interaction databases and protein-gene association databases, and can evaluate the molecular interaction of the drug to find out new pharmaceutical effects of the drug with higher precision and sensitivity, whereby a time and cost for the development of new drugs can be reduced.

The invention discloses a drug repositioning method for a COVID-19 treatment drug and application thereof. The method comprises the following steps: s1, collecting a COVID-19 diagnosis and treatment scheme report, and constructing a treatment scheme data set of known COVID-19 diseases; s2, expanding drug-disease-target point relationship data; s3, standardizing entity naming and constructing a network; s4, performing network representation and association degree calculation; and s5, sorting the potential therapeutic drugs. According to the method, the drug disease similarity and the similaritybetween the drug targets are considered, and meanwhile, the drug network structure similarity and the target network structure similarity are combined, so that the prediction accuracy of the drug target interaction relationship is improved. Potential drugs for treating COVID-19 diseases are mined on the basis of the constructed COVID-19 data set, and the potential drugs contributing to COVID-19 treatment in the drugs on the market can be effectively found.

The invention discloses a drug-disease relation identification method, system and device. The method includes the following steps that: a drug-disease relation two-dimensional matrix and/or grayscaleimage corresponding to a drug-disease relation to be identified is acquired; and the drug-disease relation two-dimensional matrix and/or the grayscale image is inputted into a convolutional neural network for processing, and an identification result is obtained. The system includes an acquisition module which is used for acquiring a drug-disease relation two-dimensional matrix and/or grayscale image and a processing module which is used for inputting the drug-disease relation two-dimensional matrix and/or grayscale image into the convolutional neural network for processing so as to output an identification result. The device includes a memory that stores at least one program and a processor that executes the at least one program. According to the drug-disease relation identification method, system and device of the present invention, the processing function of the convolutional neural network is utilized, and therefore, a drug-disease treatment relationship can be identified quickly and efficiently, potential drug-disease interaction effects can be identified, and lead compound identification and drug relocation research can be conducted. The identification method, system and device of the present invention are widely applied to the computer aided drug design field.

A computer implemented system and method for matching drugs and diseases and generating a weighted relationship between the matched drugs and diseases. The system stores a quantity of patient medical history billing records identifiable as patient prescription claim records and medical claim records. The system also stores a grouping of drug codes and groupings of diagnosis codes. The system is configured to match drugs identified in a specific patient's prescription claim records with diseases identified in the patient's medical claims. The system generates a weighted relationship between the matched drugs and diseases by calculating a link weight in accordance with a preprogrammed formula for each occurrence of the diagnosis codes identified in the patient's medical claims that is identified as associated with the disease identified and the drug upon which the query is being processed. The link weight provides a statistical match association value to each of the matched diseases.

The invention discloses a traditional Chinese medicine formula for relieving hypertension and relates to the technical field of traditional Chinese medicine formulae. The traditional Chinese medicineformula is characterized by consisting of the following raw materials in parts by weight: 20 parts of American ginseng, 10 parts of pine needles, 10 parts of radix codonopsis pilosula, 10 parts of radix ophiopogonis and 5 parts of Chinese magnoliavine fruits. The traditional Chinese medicine formula has the beneficial effects that the traditional Chinese medicine formula is adopted, respective effects of the traditional Chinese medicine components are utilized and matched with one another, and blood pressure of a patient suffering from hypertension can be effectively controlled; the medicine can be taken by the patient for a long time, is good in security and free of toxic or side effect; and for a patient suffering from sudden blood pressure increase, a hypotensive drug can be additionally taken to reduce the blood pressure rapidly, and the medicine can be taken to keep the blood pressure stable in long-term treatment, the blood pressure can be kept at a normal level, and complications caused by unstable blood pressure can be retarded.

The invention relates to an application of terramycin in treatment of acute gastroenteritis of bamboo rats, and belongs to the technical field of drug disease prevention of bamboo rats. The application is characterized in that in the case of a pathogenetic condition, 0.125g of flaky terramycin is crushed and is mixed with 3.125g of feed, the mixture is fed to each rat at each time for twice a day, and the dosage is continuously given for three days. Or, veterinary oxytetracycline hydrochloride solution is injected in leg muscle once a day, 0.4ml of veterinary oxytetracycline hydrochloride solution is injected at each time, and the bamboo rats can recover after being continuously injected for two days. The application provided by the invention has the beneficial effects that the terramycin is good in effect of treating acute gastroenteritis of bamboo rats and quick becomes effective.

The invention discloses a drug disease correlation analysis method based on time factors, and belongs to the technical field of application of complex networks in disease analysis. The drug disease correlation analysis method based on the time factor comprises: firstly, taking the number of the patients as the weight to measure the correlation between the drug and the disease, and then obtaining the positive and negative correlation between the drug and the disease by analyzing the drug use time and the diagnosis time of the patients. The drug disease correlation analysis method based on the time factor can make up for the defects in disease and drug correlation research, provides a direction for experimental research of research after drugs come into the market, and has good popularization and application value.

The invention relates to a drug disease matching database. The database comprises a drug information database, a matching database, a disease information database and an interaction module, wherein the drug information database is used for storing all drug information data; the matching database is used for storing related data of the drug treatment diseases; the disease information database is used for storing information data of all diseases, including symptoms and complications corresponding to the diseases, names and aliases of the diseases and the like, the matching database is in communication connection with the medicine information database and the disease information database, and the matching database is further in communication connection with an interaction module; the interaction module inputs disease information of a medicine needing to be searched, the disease information can be symptoms or confirmed specific disease names, and the matching database confirms a to-be-analyzed disease according to data stored in the disease information database. After the disease is confirmed, the medicine information related to the disease to be analyzed is called from the medicine information database, and a treatment scheme is generated.

The invention provides a functional network characteristic analysis method based on breast cancer diseases. The method comprises the following steps: step one, integrating various relationship networks including a drug-disease network, a drug-drug network, a drug-target network, and a target-target network and carrying out a series of network topology structure analyses on the networks; step two,on the basis of the e topological structure relation of breast cancer functional networks, digging 11 kinds of pieces of characteristic information capable of describing the drug-target mutual interaction relationship; and step three developing a related breast cancer functional network feature extraction tool. According to the invention, a functional network analysis method for characteristics ofbreast cancer diseases is established to solve a problem of relocation of the drugs; and the potential targets and new drug uses are predicted by using the method, so that the good prediction effectis obtained.

According to the medicine disease matching method based on the database, a disease name of the treatment medicine needing to be obtained is input, the matching database matches the corresponding disease data from the disease information database according to the disease name, and the medicine data corresponding to the disease data is obtained; the matching database acquires the required therapeutic drugs from the drug information database according to the drug data and generates the therapeutic scheme, and the side effects of the drugs and complications of diseases need to be considered in theprocess of generating the therapeutic scheme, so that the therapeutic scheme is more practical.