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693 – Recent Advances in Image Analysis
Skin Cancer and the Solar Cycle: An Application of Kolmogorov-Zurbenko Filters
Edward Valachovic
SUNY at Albany
Igor Zurbenko
SUNY at Albany
Skin cancer is diagnosed in more than 2 million individuals annually in the United States. It is strongly associated with Ultraviolet exposure, with melanoma risk doubling after one blistering sunburn. Solar activity, characterized by features such as irradiance and sunspots, undergoes an 11 year solar cycle. Strong random noise necessitates the analysis of long time scales, yet these account for relatively small variation when compared to shorter time scales such as daily and seasonal cycles. Kolmogorov-Zurbenko filters, applied to the solar cycle and skin cancer data, separate the components of different time scales to detect weaker long term signals and investigate the relationships between long term trends. Analyses of cross correlations reveal epidemiologically consistent latencies between variables which can then be used for regression analysis. This method reveals that strong numerical associations, with correlations >0.5, exist between these small but distinct long term trends in the solar cycle and skin cancer. This permits modeling and forecasting skin cancer trends on long time scales despite strong shorter time scale variation and the destructive presence of noise.