A retrospective analysis of the utility of an artificial neural network to predict ED volume.

Objective: The objectives of this study are to design an artificial neural network (ANN) and to test it retrospectively to determine if it may be used to predict emergency department (ED) volume.

Methods: We conducted a retrospective review of patient registry data from February 4, 2007, to December 31, 2009, from an inner city, tertiary care hospital. We harvested data regarding weather, days of week, air quality, and special events to train the ANN.

Genetic approaches to polycystic ovarian syndrome.

Purpose Of Review: This review clarifies the challenges facing investigators in the search for polycystic ovarian syndrome candidate genes.

Recent Findings: Evidence for fibillin 3 has emerged as a polycystic ovarian syndrome candidate gene. The sex hormone binding gene also shows promise, as does evidence for fetal programming and X-chromosome inactivation.

Genetics of polycystic ovarian syndrome.

Polycystic ovarian syndrome is a complex disorder with multiple factors affecting its etiology. Elucidation of specific genes and mode of inheritance remains a significant challenge. Linkage and association studies have resulted in over 50 candidate genes as a source of heritable predisposition; however, small sample sizes and failure to reproduce results have hindered efforts.