Diagnoses Breast Cancer Disease by Using fuzzy artmap (Comprehensive Journal of Science, 2025)
This research concentrated on creating a fuzzy ARTMAP classifier to categorize breast cancer instances. The fuzzy ARTMAP is a neural network family, a component of artificial intelligence structures designed for continuous supervised learning of recognition classes. Deriving knowledge and insights from datasets, meaning data mining, has gained considerable interest within the database sphere to forecast emerging data patterns for undiagnosed patient conditions. This paper introduces a method for diagnosing breast cancer illness using an algorithm encompassing several facets of actual data. Thus, this setup aids pathologists when addressing disease diagnosis, particularly where certain signs of this cancer are not readily apparent. The algorithm offers the chance to utilize trained and tested historical data to construct a framework. The software's outcome proves accurate for analysts to support them in clinical decision-making tools.
Keywords: fuzzy artmap, epoch, supervised learning, missing value.fuzzy artmap, epoch, supervised learning, missing value.