A webinar for all cardiovascular researchers interested in understanding the relevance of arrhythmia detection and improving data analysis in the preclinical research setting.

Traditional methods for locating and classifying arrhythmias relied on manual review of all ECG complexes in a dataset — an inefficient process for studies with large amounts of data and/or subjects. Because of this challenge a number of tools have been designed to automate and improve the process of data review and analysis pertaining to arrhythmia detection. Data Insights Software was designed to improve efficiencies in locating, presenting and reporting on data patterns and abnormalities for more accurate, consistent results. The goal of this webinar is to discuss common challenges and how scientists can improve their data analysis process through the application of Data Insights software.

In this exclusive webinar sponsored by Data Sciences International, experts discuss their experiences using Data Insights software showing how they have leveraged data location, classification and reporting functions to advance their data analysis process. Dr. Belal A. Mohamed (University of Goettingen) discusses how arrhythmia scoring correlates with the stage of myocardial remodeling in mice. In addition, Henry Holzgrefe (Charles River Labs) presents his research on dose dependent polymorphic arrhythmia detection in dogs.s designed to improve efficiencies in locating, presenting and reporting on data patterns and abnormalities for more accurate, consistent results. The goal of this webinar is to discuss common challenges and how scientists can improve their data analysis process through the application of Data Insights software.