Abstract: An electronic platform to measure a maturity or level of an entity in view of regulatory and business risks relating to regulatory compliance. The methods and systems can collect various data (e.g., regulatory agency reports, regulatory agency warning letters (e.g. FDA warning letters), internal and vendor company audit results, fines and settlement information, country business risks, regulatory agency product recalls, etc.) from various different data sources. The collected information is analyzed using machine learning techniques to determine a risk compliance level or score for one or more of an entity's companies, functions, control types, and locations arising from regulatory audit non-conformances. The risk compliance scores can be used to generate a risk prediction and identify one or more actions to be taken by the entity to improve or increase an associated compliance level.

Abstract: An electronic platform to measure a maturity or level of an entity in view of regulatory and business risks relating to regulatory compliance. The methods and systems can collect various data (e.g., regulatory agency reports, regulatory agency warning letters (e.g. FDA warning letters), internal and vendor company audit results, fines and settlement information, country business risks, regulatory agency product recalls, etc.) from various different data sources. The collected information is analyzed using machine learning techniques to determine a risk compliance level or score for one or more of an entity's companies, functions, control types, and locations arising from regulatory audit non-conformances. The risk compliance scores can be used to generate a risk prediction and identify one or more actions to be taken by the entity to improve or increase an associated compliance level.

Abstract: An expert system which provides one or more suggested treatments for a patient with physical trauma is disclosed. The system includes a computing device having a memory, a plurality of data bases in the memory, an application program and an inference engine program. The data bases include graphical illustrations of different types of physical trauma, and a knowledge base which contains treatment information. The application program is executed in the computing device and interactively displays a series of screens including at least some of the graphical illustrations, to elicit responses from the user concerning the specific types of physical trauma and specific characteristics of the patient. The inference engine program, which is also executed in the computing device, uses the knowledge base and information related to the responses elicited from the user, for selecting one or more suggested treatments.