1. A computer-implemented electrocardiogram (EKG) diagnosis system, comprising: a sequence analysis system for identifying EKG data patterns in raw EKG data and clustering the EKG data patterns into clusters of EKG data patterns, wherein the EKG data patterns include a PR interval, a PR segment, an ST segment, a QT interval, and P, QRS, T, and U waves, wherein each of the clusters comprises a plurality of EKG data patterns, and wherein each of the EKG data patterns within a cluster shares a similar pattern signature, and has a dissimilar pattern signature from EKG data patterns outside the cluster; a predictive analysis system for generating a predictive model for each cluster of EKG data patterns; a system for associating a diagnosis with each cluster, wherein the diagnosis is one of a healthy condition or one of at least one predefined health condition, wherein the predictive model provides a probability determined based on a radial basis function that the pattern signature of each of the plurality of clusters is representative of the diagnosis; and a system for outputting diagnostic data for each cluster of EKG data patterns, wherein the diagnostic data includes the probability that the pattern signature of each of the plurality of clusters is representative of the diagnosis.