105 results about "Longitudinal data" patented technology

A system and method for tracking longitudinal data for the maintenance and management of health of an individual. The method entails marking numerous groceries, drugs, beverages, etc., with labels that may be read by a scanner or reader embedded in a PDA or cell phone or similar small electronic device, and providing users with a suitable scanner or reader. Users scan the labels of the products they consume during the course of a day, and the system keeps track of calories, fat content, carbohydrate content, etc. of the food consumed, drug content of the drugs consumed, etc. The system can also be operated to track exercise levels and energy expenditure during the day. The system is operable to provide a comparative display of various databased information, such as calorie intake versus calorie expenditure during exercise.

A computer-implemented method for generating a longitudinal data profile from multiple disparate data sources is provided. The method includes storing, at a central data hub, first de-identified data received from a first data source, the first de-identified data including a plurality of data records having encrypted identifying data and an anonymous ID assigned to each record, wherein the anonymous ID is assigned based on a master list that includes a list of identifiers and corresponding anonymous IDs for each identifier. The method further includes storing second de-identified data received from a second data source, and storing third de-identified data received from a third data source. The method further includes processing the first, second, and third de-identified data to link the first, second, and third de-identified data using the anonymous ID, and generating the longitudinal data profile from the linked first, second, and third de-identified data.

A longitudinal database of de-identified patient healthcare transaction data records linked by longitudinal linking tags (IDs) is provided. A new healthcare transaction data record, which may include alphanumeric identification code attributes, third party attributes and/or demographic attributes, is assigned an linking ID associated with a previous healthcare transaction data record based upon successful comparison of either a designated set of identification code attributes or a designated set of demographic attributes. The longitudinal data base is assembled by a matching process in which a new data record is compared level by level with previous healthcare transaction data records through a hierarchy of a first series of matching levels each defined by a designated set of alphanumeric identification code attributes and a second series of matching levels each defined by a designated set of attributes including demographic attributes and then assigned the ID associated with a successfully matched reference data record.

The disclosed technology enables, among other things, the identification of persons and the characterization of mental perceptions (e.g., pain, fatigue, mood) and/or intent (e.g., to perform an action) for medical, safety, home care, and other purposes. Of significance are applications that require long-term patient monitoring, such as tracking disease progression (e.g., multiple sclerosis), or monitoring treatment or rehabilitation efficacy. Therefore, longitudinal data must be acquired over time for the person's identity and other characteristics (e.g., pain level, usage of a cane). However, conventional methods of person identification (e.g., photography) acquire unnecessary personal information, resulting in privacy concerns. The disclosed technology allows measurements to be performed while protecting privacy and functions with partial or incomplete measurements, making it robust to real-world (noisy, uncontrolled) settings, such as in a person's home (whether living alone or with others).

A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

The invention discloses a chronic disease condition change event prediction device based on a recurrent neural network, and the device comprises a memory, a processor, and a computer program, a preprocessing module and a chronic disease condition change event prediction model are stored in the memory, and the prediction model comprises a preprocessing module, a condition feature extraction module,and a classification module. When the processor executes a computer program, the following steps are realized: receiving long-term longitudinal data generated by multiple hospitalization of a patient, performing data preprocessing on the number by the preprocessing module, and reconstructing the data of each hospitalization into a feature vector as a to-be-tested data set; Taking the to-be-detected data set as input, extracting disease characteristics by a disease characteristic extraction module, and inputting the disease characteristics into a classification module; And enabling the classification module to output the prediction probability of various events indicating that the illness state changes. The prediction device can predict the event that the chronic disease patient has markeddisease condition change in the target time window, thereby assisting the doctor to formulate reasonable diagnosis and treatment measures and reducing the medical expenditure.

The business performance management platform system and method enables the capture, extraction, data auditing and data validation processes, combined cost accounting and analytical reporting of data required for certain combined financial, clinical operations, physician encounter, patient encounter, electronic health record, and quality of patient care measures; provides close to real-time data access and performance results; provides financial, operational, clinical, physician encounter, patient encounter, electronic health record, and quality performance dashboards and scorecards, summary level reports, Ad hoc reporting, alerting, emailing, and automated reporting and email distribution, alerting, and modeling functions. The results generated from the business performance management platform provide users of the system critical understanding of detailed and summary level data and information, such as: profit/loss characteristics across the longitudinal data elements associated with patient and physician level detail; cost at patient and physician level; expected revenues; payer performance from payer sources and clinical operations performance.

Disclosed is a computerized decision support system and method for a) tracking participation within programs, b) capturing participant's participation activity and assessment information in a format that can be easily analyzed and c) distilling the participation and assessment data into useful management and evaluation information. The repository of longitudinal data can be analyzed and reported for case-management and program-evaluation purposes. An assessment module enables analyzable assessment instruments to be custom-defined by the system user, e.g. a program manager. The customized assessment instrument is used to provide answer-restricted questions during an assessment interview, enabling virtually any data item to be tracked historically. The system captures date/time-stamped participation information at various levels of detail and stores this information in a way that can be easily retrieved and analyzed for program and participant-focused analysis. A set of industry-standard participation events can be tracked, with supporting detail, as well as less-data-intensive ad hoc user-defined activities. The data model underlying the system, and the implementation of this model within a relational database system, provides a great degree of flexibility, adaptability and efficient navigation through the database for analysis and reporting. Though numerous program-evaluation reports are provided, a set of intermediary aggregations of data is also available for efficient evaluation of additional program outcome measures.

The invention discloses a snakelike motion detection and analysis system of a high-speed-train bogie and a method thereof. The system aims at analyzing the snakelike motion state of the high-speed-train bogie in different environments and different work conditions and reasons for generation of the snakelike motion and effects of the snakelike motion on operation security of the high-speed train. Bogie transverse and longitudinal acceleration signals are acquired through a transverse two-dimension acceleration sensor and a longitudinal two-dimension acceleration sensor, which are arranged on the bogie of the system and storage of characteristic data is performed through filtering of the signals by a real-time data acquisition controller and the analysis result and trend are transmitted to a train display terminal through a train transmission network. Therefore, long-term tracking and trend analysis of the bogie transverse and longitudinal data are realized and occurred faults of the bogie are monitored and alarmed in a real-time manner.

An embodiment of the invention provides a double-gate TFT (thin film transistor) substrate and a production method thereof, which relate to the field of liquid crystal display manufacturing. IC (integrated circuit) connectors can be reduced while green defects are prevented, and pixel aperture ratio can be increased. The double-gate TFT substrate comprises a glass substrate, transverse gate lines, meshed Vcom (visual communication) lines and longitudinal data lines. The Vcom lines in each row of the meshed Vcom lines in electrical connection, and the Vcom lines are electrically connected with IC (integrated circuit) elements through Vcom line IC connectors. If the number of the data lines is N, the number of the Vcom line IC connectors is larger than 0 and smaller than N+1. At least one group of the corresponding Vcom lines between each two adjacent rows of the Vcom lines is longitudinally electrically connected. The double-gate TFT substrate and the production method thereof are used for producing TFT substrates.

A system and method for the assembly of a longitudinally linked database of patient healthcare data records involve a neutral implementation partner to ensure that sensitive patient-identifying information contained in the data records is secure at all times. The implementation partner is deployed to mediate processing of the data records in a secure environment, which is inaccessible to unauthorized parties including data supplier and database facility personnel. At data supplier sites, the implementation partner mediates processing of the data records so that the patient-identifying attributes in the data records are encrypted before they are transmitted to a common longitudinal database facility. At the common longitudinal database facility, the implementation partner mediates processing of the data records so that internal tags are assigned to data records based on the values of the encrypted patient-identifying attributes. The internal tags are used to longitudinally link the encrypted data records in a statistically meaningful manner. The implementation partner may be any combination of software, hardware and organizational entities.

The invention relates to a deskew display panel comprising transverse scanning lines, longitudinal data lines and sub-pixels. The sub-pixels are distributed between the adjacent scanning lines and the data lines in arrays, and each mXn sub-pixels form a pixel unit. Each sub-pixel comprises a transistor, a grid of the transistor is connected with the scanning lines, a source electrode is connected with the data lines, and a drain electrode is respectively connected with two capacitors. Corresponding transistors of the sub-pixels of each pixel unit are connected in the same way. The data lines connected with the source electrodes in the pixel units are respectively connected with the two adjacent sub-pixels in a same row, and the source electrodes of the two sub-pixels are respectively connected to the upper and lower scanning lines. During color blending, skew degree is effectively suppressed, color display effect of the display panel is improved, and the deskew display panel is particularly applicable to a narrow-frame display.

The invention discloses a fire-extinguishing scheduling method and system for fire-fighting robots of an electric tunnel. The scheduling method comprises the following steps: obtaining tunnel ambientcondition data, and adopting a transverse data fitting and longitudinal data fitting method to pre-judge a suspected fire source position and strength according to the tunnel ambient condition data; scheduling a video robot to be close to the suspected fire source position within a safety distance to judge a development stage of a fire behaviour; scheduling the surrounding fire-fighting robots ina unified mode according to the determined development stage of the fire behaviour and strength of the fire behaviour, and scheduling the fire-fighting robots to a fire behaviour site to perform fire-fighting fire-extinguishing treatment; and scheduling the fire-fighting robots which complete spray to withdraw from a fire source site, obtaining fire behaviour continuous monitoring data of the video robot in real time, and performing secondary fire-extinguishing treatment once after-combustion occurs. The fire-extinguishing scheduling method and system can realize automatic fire behaviour monitoring and fire extinguishing, guarantee safe operation of power equipment without staff on duty and human intervention, greatly reduce labor cost, and improve working safety of personnel.

The invention discloses a space-time cooperation segmentation method based on an infant brain tumor multi-modal MRI graph. The space-time cooperation segmentation method includes (1) obtaining the postoperation brain tumor MRI images; (2) mapping the vertical data to the time domain and the spatial domain for segmentation; wherein the time domain segmentation includes obtaining the pre-operation segmentation result and the vertical data to be segmented, aligning the pre-operation and postoperation images, and constructing a postoperation tumor growth model; and the spatial domain segmentation includes constructing a healthy infant brain template, extracting the Haar structure characteristics, obtaining the preliminary probability result through the combination of a structure random forest method and an AdaBoost frame, increasing labels by means of similarity area increasing algorithm, and obtaining the spatial domain segmentation result; and (3) constructing a four-dimensional graph model through the combination of the time domain segmentation result and the spatial domain segmentation result, and optimizing the obtained parameters to form an automatic segmentation result. The segmentation method improves the accuracy of the infant brain tumor area segmentation.

The invention provides a high-precision GPS positioning point obtaining method and system. The method comprises: a GPS positioning point data set is obtained; non-effective bits of longitudinal data and latitude data in the GPS positioning point data set are removed by using a preset precision factor; on the basis of the precision factor, unit zones of histograms are set and histogram statistics is carried out on the longitudinal data and latitude data after correction; according to the histograms of the longitudinal data and latitude data after correction, a corresponding zone with the largest GPS positioning point number among a preset number of continuous unit zones is obtained, and GPS positioning point data sets corresponding to the correction data in the zone are obtained and are marked as a first set and a second set; and after corresponding correction and statistics are carried out on the GPS point data in the first set and the second set, a third set and a fourth set that have the largest GPS positioning point number are obtained. Therefore, the third set and the four set that are close to GPS accurate point relatively are obtained, so that the precision is improved substantially.

The invention discloses a cluster-based automatic WMH extraction system. The system comprises a tissue type segmentation module, a DARTEL standard segmentation module, a non-brain tissue removal module, a WMH segmentation module and a WMH refined division module, wherein the tissue type segmentation module is used for preprocessing a plurality of RLAIR images and a plurality of T1 images of a plurality of participants; the DARTEL standard segmentation module is sued for mapping the images obtained by the tissue type segmentation module into a DARTEL space; the non-brain tissue removal module is used for removing non-brain tissues of the FLARI images and the T1 images in the DARTEL space, and respectively marking the obtained images as D-FLAIR images and D-T1 images; the WMH segmentation module is sued for segmenting the D-FLAIR images and the D-T1 images on the basis of the DARTEL space so as to obtain a WMH map; and the WMH refined division module is used for carrying out refined division on the WMH map so as to obtain an intracerebroventricular white matter hyperintensities area PVWMH and a deep white matter hyperintensities area DWMH. The system is an automatic WMH extraction system which is capable of segmenting white matter focuses on the basis of longitudinal data sets and carrying out refined division on the WMH and has favorable generalization performance.