Can paroxysmal atrial fibrillation be predicted? That’s the question
PhysioNet (NIH/NCRR Research Resource for Complex Physiologic Signals) and Computers in Cardiology want to answer in its 2001 CinC Challenge 2001. This is the second in a series of annual open contests aimed at catalyzing research, friendly competition, and wide-ranging collaboration around clinically important problems. Prizes will be awarded to the most successful participants.
The challenge is to develop a fully automated method to predict the onset of paroxysmal atrial fibrillation/flutter (PAF), based on the ECG prior to the event. Atrial fibrillation is associated with increased risk of stroke and cardiac disease, and is the most common major cardiac arrhythmia, affecting an estimated 2.2 million people in the United States alone. Currently, no reliable validated methods exist to predict the onset of PAF. Given recent advances in clinical electrophysiology, a prediction tool that would allow for detection of imminent atrial fibrillation is an important step toward the application of targeted therapies that may increase longevity and improve the quality of life for many people.
Typically, those interested in working on such problems must undertake a costly and time-consuming effort to collect and to assess the necessary data, a prerequisite that excludes many researchers and students who might otherwise make important contributions to the field. PhysioNet and the NIH/NCRR seek to eliminate this barrier to research by providing large, well-characterized, and freely available data sets for the study of important unsolved problems in analysis and modeling of physiologic signals and time series, including the problem posed by CinC Challenge 2001. For details of the contest rules, background information, data, and software, please visit PhysioNet (http://www.physionet.org/).