440 results about "Disease risk" patented technology

Methods for determining statistical models for predicting disease risks of a population are provided. Two types of data associated with members of the population are collected. The data may include both genetic and non-genetic types of data. A candidate statistical model is selected for calculating the disease risk. The model has a plurality of parameters and is a function of only one of the two types of data. A data weight is determined for each member of the population. Members having like data of the other type have like weights. The parameters of the model are optimized by fitting the collected data to the model taking into account of the weights.

The invention provides a method and a system for predicting cardiovascular and cerebrovascular disease risks. The method comprises the following steps: step 1, defining problems of cardiovascular and cerebrovascular disease prognosis risk prediction, step 2, collecting health medical data of cardiovascular and cerebrovascular disease patients; step 3, preprocessing data, including data integration, data cleaning, and processing missing data; step 4, constructing features and selecting features, identifying potential risk factors; step 5, the identified risk factors and rehabilitation outcomes forming an input-output sample set, inputting the input-output sample set to a random forest algorithm for model training, and evaluating prediction performance of a model. The method and the system can obtain health medical data of cardiovascular and cerebrovascular disease patients, the data being required by a clinician input model, and a predicted rehabilitation outcome of a patient in a certain time period in future is obtained through the model. The method and the system can preferably predict prognosis risks, so as to realize personalized accurate rehabilitation treatment.

The use of a medical software platform to collect, normalize, and aggregate clinical data. Supports clinical care and provides research and clinical tools for institutions, healthcare providers, researchers, and patients. The invention provides a graphical interface to customize searches in the database for specified subsets of conditions, treatments or outcomes. The invention also provides a system and method for searching through clinical databases for desired terms which may provide additional information to a physician regarding patient care. Furthermore, this invention facilitates personalized medicine-based practices as relationships between genetics, personal heath data from multiple sources, disease risk and drug response can be more easily visualized and utilized for patient care and research.

A method and system use a combined contribution of multiple disease risk factors to predict the risk of onset of particular diseases in an individual. The prediction models use information from separate studies. Multiple disease predictions for a predetermined number of diseases are made. The predictions are used to calculate the individual's mortality risk and life expectancy. The life expectancy is compared to that of age and gender matched peers to determine the inner age of the individual.

The invention relates to methods and biomarkers for assessing a subject's risk for a disease, such as cancer, an autoimmune disease or a neurological disease. In particular, the invention provides methods and biomarkers for creating exon copy number variation (ECNV) profiles, and determining disease risk according to the subject's ECNV profiles.

Compositions are provided that include water soluble or water dispersible film shreds, a carrier and an active, such as, but not limited to a drug, flavoring agent or coloring agent. Also provided are methods of use of the film shreds, such as in improving the dissolution, stability, aesthetics, or taste of a composition or its components, and in reducing a disease risk associated with an active.

The invention relates to a health risk assessment and disease early warning information system, and belongs to the technical field of health management. The system comprises an employee health management system and a personal health system; the employee health management system comprises 11 modules such as an employee basic information management module, an employee health data acquisition module,and an employee health questionnaire management module; the personal health system consists of an ordinary user registration sub-module, a personal information management sub-module, a personal health history management sub-module, a daily health monitoring sub-module, a medical sick rest management sub-module, a health questionnaire sub-module, an annual health examination sub-module, a health condition assessment sub-module, a disease risk assessment sub-module, a health promotion management sub-module, and a health consultation forum sub-module. The health risk assessment and disease earlywarning information system forms an integrated network management mode of health management, health risk assessment and health risk intervention control.

Provided are methods for determining concurrently with a simple, minimally invasive test, the adequacy of pancreatic beta-cell compensation and/or the presence of tissue insulin resistance in a subject human or an experimental animal. The methods allow for the determination of a subject's or experimental animal's susceptibility to developing type 2 diabetes mellitus (DM2) or to progression to more advanced forms of DM2. Among other uses, the methods allow for diagnostic classification of subjects for decisions regarding therapeutic interventions, clinical differentiation between type 1 DM and DM2, clinical monitoring of treatments intended to reduce risk of developing DM2 in non-diabetic subjects, clinical monitoring of agents intended to improve existing DM2 and to prevent progression of DM2, clinical development and testing of new compounds, candidate agents, or candidate therapies for preventing progression to DM2 or disease progression in existing DM2, and preclinical screening of candidate agents or candidate therapies in experimental animals to identify and characterize agents having insulin-sensitizing properties, pancreatic stimulatory or regenerative properties or other desirable actions.

The invention relates to a big data health prediction system. The system comprises a data information collection module, a big data analysis platform and an intelligent terminal, wherein the data information collection module is used for collecting user health feature data information; the big data analysis platform builds a disease risk prediction model with high accuracy by utilizing a machine learning method, performs prediction and disease risk assessment on a health state of a user according to the built disease risk prediction model, and gives guiding views of the health state of the user; the intelligent terminal is used for receiving a final disease prediction result and the guiding views of the health state of the user obtained by the big data analysis platform; and the user can upload the health feature data information to the big data analysis platform through the intelligent terminal in real time. The user can prevent own health problems according to the guiding views of the health state of the user, thereby guaranteeing health of the user; and the system is relatively high in practicality and high in accuracy.

A dietary supplement is created, comprised of material from the following nutrients, vitamins, herbs, minerals, and food and plant substances and food and plant derivatives: lycopene, vitamin E, selenium, green tea, coenzyme Q10, garlic, folic acid, vitamin C, curcumin, seaweed, Cordyceps sinsensis mushroom, Lentinus edodes (shiitake) mushroom, and Ganoderma lucidum (reishi) mushroom. The composition is administered orally for individuals who wish to reduce their risk of disease, particularly cancer-risk.

A disease risk evaluation and education tool, preferably implemented in logic on a computing device such as a Personal Digital Assistant, permits a user to input patient-specific data relevant to evaluating that patient's risk for a particular disease, e.g., coronary heart disease. The tool's logic calculates the equivalent age of the patient, based on the Framingham data set and on the input data, and presents one or more treatment recommendations.

The present invention uses spectroscopic tissue volume measurements using non-ionizing radiation to detect pre-disease transformations in the tissue, which increase the risk for this disease in mammals. The method comprises illuminating a volume of selected tissue of a mammal with light having wavelengths covering a pre-selected spectral range, detecting light transmitted through, or reflected from, the volume of selected tissue, and obtaining a spectrum of the detected light. The spectrum of detected light is then represented by one or more basis spectral components, an error term, and an associated scalar coefficient for each of the basis spectral components. The associated scalar coefficient is calculated by minimizing the error term. The associated scalar coefficient of the each of the basis spectral components is correlated with a pre-selected property of the selected tissue known to be indicative of susceptibility of the tissue for the pre-selected disease to obtain the susceptibility for the mammal to developing the pre-selected disease.

The invention relates to a clinic remote service system based on artificial intelligence. The system comprises the components of a clinic terminal, a cloud server, a patient terminal, a doctor terminal, a self-service medicine selling terminal, a medicine selling user terminal and a commodity supplementing terminal. The clinic terminal, the patient terminal, the doctor terminal, the self-service medicine selling terminal, the medicine selling user terminal, the commodity supplementing terminal and the cloud server perform data transmission through a network. The clinic remote service system has advantages of establishing a novel medical service system, settling problems of preliminary diagnosis and treatment and health management of a patient, realizing a one-station medical health preserving solution which comprises medical health examination, AI disease diagnosis, inquiry consultation, electronic medicine commerce, chronic disease management, saving diagnosis time and diagnosis cost,and reducing disease risk.

The invention relates to a disease risk predication method and system. The method comprises the following steps of: S1, receiving input gene sequencing result information; analyzing the input gene sequencing result information to obtain all mutant gene information; S2, looking up disease gene mutant information of corresponding gene sites from a precision medical knowledge base according to the gene sites corresponding to the mutant gene information, so as to obtain at least one piece of disease gene mutant information; S3, matching each piece of the disease gene mutant information with all the disease gene mutant information to obtain the similarity of each piece of the mutant gene information, and all the disease gene mutant information; and S4, obtaining a risk predication table aiming at the gene sequencing result information according to the similarity of each piece of the mutant gene information, and all the disease gene mutant information. By analyzing an association relation of susceptibility genes, mutation sites, mutation types and diseases, disease risk predication is carried out on healthy people and general disease risk grade predication is provided; disease risks in the future are reduced.

The present invention discloses a disease risk assessment and personalized health report generation system and method. The method comprises: inputting longitudinal health examination big data; arranging the data; defining the threshold range of various indicators of the disease according to the name of the disease, and using the sas software to establish a corresponding disease queue according to the threshold range of various indicators of the disease; and after establishing the queue, using the cox single factor regression analysis method to carry out variable selection on each variable; carrying out multi-factor regression analysis on the variables incorporated into the cox regression model; establishing a cox proportional risk model; verifying the inside of the cox proportional risk mode, and verifying the outside of the cox proportional risk model; obtaining a disease prediction model; generating a disease risk assessment hyperbola; inputting new individual physical examination indicators, generating disease risk assessment results according to the disease prediction model and the disease risk assessment hyperbola, and outputting a disease risk assessment and personalized health report according to the preset indicators.

Indole-3-propionic acid as a marker and for treatment for Huntington Disease.

Systems, methods and a software product for disease reduction education and risk assessment are disclosed. In one embodiment, a system for computer-assisted disease risk assessment and education includes a processor that generates at least a plurality of questions directed to a disease risk assessment for a user. Based upon responses received from a user, the processor is further operable to generate one or more plans configured to prospectively guide the risk behavior and sexual activity of the user. At least one personal data entry and display device (PDDA) is communicatively coupled to the processor, that is operable to at least display the plurality of questions and to accept corresponding responses from the user.

Systems and methods for identifying genetic variations in a disease and diagnosing a patient with a mental illness, or a generic variant of same. The systems and methods use genomics and phenomics in a computer-implemented methods to identify biclusters in phenomic and genomic data, discover relationships among the biclusters, organize the relations into partitions, rank the predictive utility of features, and map the disease risk function. This can in turn be used to diagnose a patient in a person-centered fashion.

This invention features our discovery on usages of Methylenetetrahydrofolate Reductase (MTHFR) gene polymorphisms in predicting homocysteine (Hcy) level and/or incidence and prognosis of diseases associated with increased Hcy level in a subject, as well as predicting treatment effects of medicines in the category of Angiotension Converting Enzyme Inhibihor (ACEI) with and without combination with B Vitamins. This invention also features our discovery on laboratory and analytical methods that are essential to the above described usages of MTHFR gene polymorphisms. In addition, this invention features a kit that has translated the above discoveries into a practical and reliable tool that can be applied to accomplish the above described usages of MTHFR gene polymorphisms. This invention represents an important step in realizing personalized medicine, with the goal to tailor diagnosis, prevention and treatment strategy to meet individual needs.