Abstract
Clinical male reproductive medical problems are particularly complex due to the variety of systems that interact to achieve the ultimate reproductive outcome, fertilization. Neural computation offers a robust nonlinear computational modeling tool for andrological data sets. In this mini-symposium, neural computation is reviewed, and aspects of neural computation are discussed, including cross-validation, overlearning and feature extraction. Real world neural computational solutions for clinical andrological problems are given, including modeling outcomes of gamete micromanipulation, testis biopsy, and outcomes after varicocele surgery.
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