4 results about "Electronic data capture" patented technology

The present invention provides a method and system for automatically and seamlessly processing clinical trial source data into electronic data capture (EDC) systems. In one embodiment, a file structure is defined for an electronic binder system (eBinder); source data is uploaded to the eBinder; the source data is encrypted, Patient Identifiable Information in the source data is masked; the source data is converted into machine readable plain text in the JavaScript Object Notation (JSON) format using Natural Language Processing (NPL) technologies; the JSON data is converted into tabulated machine readable data in the HyperText Markup Language (HTML) format using NPL technologies; the HTML data is converted into machine understandable data using NPL technologies; the machine understandable data is populated into EDC datasets using NPL technologies; the source data and converted data are displayed side-by-side for source data verification; and a platform is provided for regulatory data verification or auditing.

To provide a method of converting an Electronic Data Capture (EDC) dataset to a Standard Data Tabulation Model (SDTM) dataset.SOLUTION: A method includes a step of processing metadata for an EDC dataset, the metadata comprising EDC field names, to produce vectors of a particular dimensionality. The vectors are processed in an embedding model to produce embedded vectors of a lesser dimensionality. The embedded vectors are processed, in a prediction model, to produce class predictions for the EDC field names, the classes corresponding to SDTM field names. The EDC field names are associated with the SDTM field names based on the class predictions for the EDC field names. The embedding model is obtained from a trained Siamese neural network.SELECTED DRAWING: Figure 1

The present invention provides a method and system for automatically and seamlessly processing clinical trial source data into electronic data capture (EDC) systems. In one embodiment, a file structure is defined for an electronic binder system (eBinder); source data is uploaded to the eBinder; the source data is encrypted, Patient Identifiable Information in the source data is masked; the source data is converted into machine readable plain text in the JavaScript Object Notation (JSON) format using Natural Language Processing (NPL) technologies; the JSON data is converted into tabulated machine readable data in the HyperText Markup Language (HTML) format using NPL technologies; the HTML data is converted into machine understandable data using NPL technologies; the machine understandable data is populated into EDC datasets using NPL technologies; the source data and converted data are displayed side-by-side for source data verification; and a platform is provided for regulatory data verification or auditing.

A method implemented by a computer system for detecting personally identifiable information (PII) in clinical trial data before the clinical trial data is committed to a hardware storage device to improve data security, comprising: causing rendering of a graphical user interface for input of clinical trial data and one or more controls; receiving, through the graphical user interface, input clinical trial data; prior to committing the clinical trial data to a hardware storage device, associating, in memory, the clinical trial data associated with a pending state; upon determining that the clinical trial data does not include PII, accessing, from memory, the clinical trial data input into at least one of the one or more input portions; releasing the clinical trial data from the pending state; and committing the clinical trial data released to the hardware storage device.