142 results about "Disease severity" patented technology

A system and method of obtaining serial biochemical, anatomical or physiological in vivo measurements of disease from one or more medical images of a patient before, during and after treatment, and measuring extent and severity of the disease is provided. First anatomical and functional image data sets are acquired, and form a first co-registered composite image data set. At least a volume of interest (ROI) within the first co-registered composite image data set is identified. The first co-registered composite image data set including the ROI is qualitatively and quantitatively analyzed to determine extent and severity of the disease. Second anatomical and functional image data sets are acquired, and form a second co-registered composite image data set. A global, rigid registration is performed on the first and second anatomical image data sets, such that the first and second functional image data sets are also globally registered. At least a ROI within the globally registered image data set using the identified ROI within the first co-registered composite image data set is identified. A local, non-rigid registration is performed on the ROI within the first co-registered composite image data set and the ROI within the globally registered image data set, thereby producing a first co-registered serial image data set. The first co-registered serial image data set including the ROIs is qualitatively and quantitatively analyzed to determine severity of the disease and/or response to treatment of the patient.

The present invention provides systems and methods for monitoring subjects, especially during sleep. Respiratory and sound data are recorded and coughs arousal are recognized as joint events in both of these signals having selected characteristics. Further, cough-arousal events during sleep are recognized when a likely cough occurs in association with a recognized EEG arousal. Cough arousal events are combined into a cough arousal index that reflects disease severity and sleep disruption due to cough. The methods of this invention are computer-implemented and can be provided as a program product including a computer readable medium. Measurements and indices provided by this invention can be used to monitor and to treat respiratory diseases.

The present invention provides systems and methods for monitoring subjects, especially during sleep. Respiratory and sound data are recorded and coughs arousal are recognized as joint events in both of these signals having selected characteristics. Further, cough-arousal events during sleep are recognized when a likely cough occurs in association with a recognized EEG arousal. Cough arousal events are combined into a cough arousal index that reflects disease severity and sleep disruption due to cough. The methods of this invention are computer-implemented and can be provided as a program product including a computer readable medium. Measurements and indices provided by this invention can be used to monitor and to treat respiratory diseases.

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 present invention relates to identification and uses of biomarkers for neurodegenerative disease, including Alzheimer's disease, and the related diseases. More specifically, the present invention relates to the identification of protein biomarkers useful for the screening, diagnosis, and differentiation of Alzheimer's disease from Parkinson's disease, other neurodegenerative diseases, and normal controls, and in the monitoring of Alzheimer's disease severity and disease mechanisms in patients.

The invention relates to 12 identified protein biomarkers for diagnosis, determination of disease severity, and therapeutic response monitoring of patients with breast cancer. The method is based on the use of 2-dimensional (2D) gel electrophoresis to separate the complex mixture of proteins found in blood serum, the quantitation of up to 12 protein biomarkers, and statistical analysis of the concentration of the protein biomarkers.

The present invention provides an inhaler capable of measuring lung function, feeding back the measurements, and administering medicine suitable for a lung condition in a single use. The inhaler 1 of the present invention includes a lung function measuring unit 2 having a spirometer for measuring lung function, and, using a computing unit 5, compares the lung function measurements with a medication pattern table stored in a storage unit 7 and determines a disease severity and a diseased region of the lung. Based on the determination results, the computing unit further selects types and particle diameters of medicines suitable for the lung condition, and controls an ejection unit 3 including a plurality of ejection portions to eject the medicines required for treatment in a single use.

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.

A Disease Severity Index (DSI) is provided for assessment of chronic liver disease in a patient using non-invasive liver function test results. A DSI was derived from non-invasive liver function test results based on hepatic blood flow. The DSI is used in methods for prediction of clinical outcomes, prediction of response to antiviral treatment, and assessment of progression of chronic liver diseases. Non-invasive methods to diagnose three distinct categories of patients with Primary Sclerosing Cholangitis (PSC) are provided. The methods can be used to diagnose PSC patients as Slow Progressors, Moderate Progressors and Rapid Progressors.

Materials and Methods for stratifying disease severity and for monitoring major depressive disorder are provided.

Use of clusterin as a biomarker of Alzheimer's disease (AD), particularly methods and compositions for detection of clusterin in a biological sample and assessment of in vivo pathology, disease severity and rate of clinical progression in a subject having or suspected of having AD.

The invention discloses a large-scale medical data knowledge mining and treatment scheme recommendation system. The system comprises a data set preprocessing module which is used for obtaining real electronic medical record data and carrying out preprocessing on the electronic medical record data composed of a plurality of types of heterogeneous data sources; a disease severity prediction module which is used for obtaining disease severity scores of each patient in the treatment process; a treatment effectiveness measurement module which is used for obtaining effective treatment measurement information; a patient similarity measurement module which is used for constructing a similarity measurement relationship of patients; and a drug therapy scheme recommendation module which is used for obtaining drug therapy scheme recommendation of the next stage. According to the invention, the severity degree of the illness state of the patient is judged and predicted through the multitask bidirectional heterogeneous LSTM, the effectiveness measure of treatment is defined, the fine grit similarity of the patient is calculated, and the treatment scheme of the next stage is recommended accordingto the historical treatment records of the patient and the effective treatment schemes of other patients with high pathology similarity.

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 pharmaceutical composition for preventing and treating rheumatoid arthritis. The traditional Chinese medicine raw materials for constituting active ingredients of the pharmaceutical composition by weight are as follows: 5.5-6.0mg of berberine, 0.3-0.4mg of palmatine, 1.5-2.0mg of jatrorrhizine, 1.5-1.8mg of magnoflorine, 0.1-0.2mg of phellodendrine, 0.2-0.3mg of coptisine, 55-60mg of baicalin, 1.5-2.0mg of baicalein, 5.0-7.0mg of wogonoside, 0.03-0.05mg of wogonin, 20-25mg of geniposide, 0.1-0.2mg of crocin and 0.25-0.3mg of chlorogenic acid. The results of pharmacological tests show that the pharmaceutical composition can significantly reduce the disease severity of CIA mice with the rheumatoid arthritis, significantly improve the inflammation and the immune injury situation at lesion sites in comparison with a control group and be used for preparing drugs for preventing and treating the rheumatoid arthritis.