Abstract: Low-cost assay test strip readers enable creation of profiles of analyte reactions detected on an assay test strip utilizing a simple detector fixedly mounted to a body of the reader. The detector may be a single detector, such as a photodetector, which detects an optical signal at a single point. The assay test strip is inserted and/or removed from the test strip reader and the detector detects the optical elements of the strip during such insertion and/or removal. The movement of the test strip with respect to the body enables the detector to scan a length of the test strip, thereby generating a profile of optical signals representing analyte reactions along a one-dimensional portion of the test strip. The reader may convert the detected profile into a displayable indication of analyte concentrations for diagnostic purposes.

Abstract: Techniques for identifying representative patients from a patient group are provided. Based on an outcome of interest, one or more patients can be grouped according to phenotyping features associated with the outcome of interest. Additionally, in response to grouping the one or more patients, a representative patient of the one or more patients can be determined based on values associated with the phenotyping features.

Abstract: Techniques that facilitate improved medical condition diagnostics are provided. An example embodiment can include a device. The device can include a memory that stores computer executable components and a processor. The processor can execute the computer executable components stored in the memory. The computer executable components can include training logic component and a determination logic component. The training logic component can generate a prediction model. The prediction model can generate \predict diagnosis based on electronic healthcare record data and image data of a known patient. The determination logic component can determine whether the predicted diagnosis exceeds an accuracy threshold value.

Abstract: A method and system of imputing corrupted sequential data is provided. A plurality of input data vectors of a sequential data is received. For each input data vector of the sequential data, the input data vector is corrupted. The corrupted input data vector is mapped to a staging hidden layer to create a staging vector. The input data vector is reconstructed based on the staging vector, to provide an output data vector. adjusted parameter of the staging hidden layer is iteratively trained until it is within a predetermined tolerance of a loss function. A next input data vector of the sequential data is predicted based on the staging vector. The predicted next input data vector is stored.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate automatically mapping different data types are provided. In one embodiment, a computer-implemented method comprises: constructing, by a system operatively coupled to a processor, an index from one or more classifier models for one or more data types; scoring and ranking, by the system, one or more candidate pairs for the one or more data types based on confidence score; and analyzing, by the system, how the one or more candidate pairs are scored and automatically generating the one or more classifier models used to construct the index.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate providing treatment suggestions are described herein. In one example, a computer-implemented method comprises: generating, by a system operatively coupled to a processor, treatment directed graphs associated with a plurality of treatment regimens, wherein, in connection with generating respective treatment directed graphs, penalties are applied during weighting of respective regimens as a function of an associated confidence level; identifying a treatment directed graph that corresponds to the patient directed graph; and outputting a set of treatment suggestions associated with the treatment directed graph that corresponds to the patient directed graph.

Abstract: Techniques are provided for training and/or executing, by a system operatively coupled to a processor, a modified random forest model using a process that employs significance of data fields in performing imputation, filtering data records out of sample datasets for generating subtrees, and filtering out subtrees for making predictions.

Abstract: Techniques are provided that facilitate determining, by a system operatively coupled to a processor, respective performance scores for a first set of candidate transformation scripts based on a performance criterion, wherein the candidate transformation scripts are related to extract, transform, load (ETL) processing of a new data source to a data target. Techniques are also provided that facilitate generating, by the system, a recommendation of one or more of the first set of candidate transformation scripts based on the respective performance scores for performance of the ETL processing.

Abstract: Techniques are described that facilitate automatically providing entities with rephrased versions of standard answers. In one embodiment, a computer-implemented is provided that comprises determining, by a device operatively coupled to a processor, a talking style of a plurality of talking styles that an entity is associated with based on reception of natural language input from the entity proposing a question related to a defined topic. The method further comprises selecting, by the device based on the talking style, an answer rephrasing model from a plurality of answer rephrasing models respectively configured to generate different rephrased versions of a standard answer to the question, and employing, by the device, the answer rephrasing model to generate a rephrased version of the standard that corresponds to the talking style.

Abstract: Combination therapies are automatically discovered that provide statistically significantly greater protection against a specific outcome, compared to therapies with fewer treatments. A dataset is received that associates each of a plurality of respective individual treatments with a corresponding outcome and a corresponding set of confounding factors. A plurality of new potential combination therapies are combined iteratively. The received dataset is used to automatically identify at least one candidate combination therapy of the new potential combination therapies that provides a statistically significantly greater protection against an outcome with reference to each of the plurality of respective individual treatments.

Abstract: A system and method for augmenting or adding to the information used by an in-vitro diagnostic or other diagnostic device to generate results of a test is disclosed. A diagnostic device is capable of generating test results based on a sample, such as a sample provided by a patient, and is also capable of receiving additional information to enhance the results providable by the device. For example, an in-vitro diagnostic device is configured to read a lateral flow assay test, and is configured to receive additional diagnostic, network, test identification, or environmental information over a network. Using both the result of the diagnostic test and the additional information, the disclosed device provides more thorough, accurate, and reliable diagnostic information. The results generated by the device may be communicated to an appropriate remote device to enhance the results obtainable by such tests.

Abstract: A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.

Abstract: A method, system, and computer program product for obtaining a candidate event sequence that includes at least one event for achieving a goal, obtaining a reference event sequence, the candidate event sequence comprising at least one event that is not comprised in the reference event sequence, comparing an effectiveness of the candidate event sequence on the goal and an effectiveness of the reference event sequence on the goal, and identifying the candidate event sequence as an effective sequence for achieving the goal in response to the effectiveness of the candidate event sequence being better than the effectiveness of the reference event sequence.

Abstract: Disclosed are a computer-implemented method for converting a procedural process model for a process to a hybrid process model, a system and a computer program product. In this method, a plurality of steps of the process which are included in the procedural process model may be clustered selectively according to historical execution information of the plurality of steps, to generate a plurality of candidate cluster set. One candidate cluster set satisfying a first condition may be selected from the plurality of candidate cluster sets. Then, the procedural process model may be converted into the hybrid process model according to the selected candidate cluster set.

Abstract: A method, device, and computer program storage product for generating a query to extract clinical features into a set of electronic medical record (EMR) tables based on clinical knowledge. A knowledge tree is constructed according to a set of clinical knowledge data. An EMR graph corresponding to a set of EMR tables is obtained. The EMR graph comprises at set of table nodes and a set of attribute nodes. The set of table nodes and the set of attribute nodes represent a structure of each EMR table in the set of EMR tables and a reference relationship among attributes of set of EMR tables. A plurality of sub-queries is generated based on the knowledge tree and the EMR graph. At least one query is generated by combining the plurality of sub-queries according to the knowledge tree.

Abstract: A system is disclosed in which a plurality of in-vitro diagnostic (IVD) devices each include a network communication device for connecting to a publicly accessible data network. For example, IVD devices are provided with a cellular modem for connecting to a public cellular network. These IVD devices connect to the data network upon completion of a diagnostic test, and upload results of the test, as well as other appropriate data, to a remote device which is also on the network. The IVD devices also download appropriate data from remote network elements. The remote network element may be a network element such as a Hospital Information System (HIS) or Laboratory Information System (LIS) database. Alternatively, the remote device may be a remote server or another IVD device. This connectivity enables the system to accumulate diagnostic test data, and to analyze, report, and/or update the IVD devices based on the accumulated data.

Abstract: It is provided a method and system for supporting imperative graphic queries on a relational database, the method comprising: parsing an imperative graphic query into operations of execution plans; translating operations of execution plans which are supported by the relational database into common table expression queries; and executing the translated common table expression queries on the relational database.

Abstract: A system and method for augmenting or adding to the information used by an in-vitro diagnostic or other diagnostic device to generate results of a test is disclosed. A diagnostic device is capable of generating test results based on a sample, such as a sample provided by a patient, and is also capable of receiving additional information to enhance the results providable by the device. For example, an in-vitro diagnostic device is configured to read a lateral flow assay test, and is configured to receive additional diagnostic, network, test identification, or environmental information over a network. Using both the result of the diagnostic test and the additional information, the disclosed device provides more thorough, accurate, and reliable diagnostic information. The results generated by the device may be communicated to an appropriate remote device to enhance the results obtainable by such tests.

Abstract: A method, system, and computer program product, include obtaining a plurality of training sets of samples and a plurality of testing sets of samples from a data set of clinical records, the plurality of training sets of samples and the corresponding plurality of testing sets of samples including different samples of the data set, determining statistical significance for a plurality of risk factors of a model from the plurality of training sets of samples, determining a plurality of performance metrics of the model from the plurality of testing sets of samples, and determining an evaluation metric of the plurality of risk factors for the model based on the statistical significance and the plurality of performance metrics, the evaluation metric being for improving accuracy of the model.

Abstract: This disclosure provides a computer-implemented method for code suggestion. The method comprises collecting a set of runtime context features of a program that is being edited. The method further comprises comparing the set of runtime context features with at least one set of stored context features to find at least one matching set of stored context features. Each of the at least one set of stored context features is extracted from a corresponding code segment. The method further comprises presenting at least one code segment with its set of stored context features matching the set of runtime context features, for the user to choose to add into the program.