Abstract

The primary objective of this research work is to develop an expert system for identification & classification of the cervical cells in the images of the slides of Papanicolaou smear test, which is done for screening of cervical cancer. The expert system can serve as a potential tool for mass level screening of cervical cancer by characterization and classification of Papanicolaou smear images. The Expert system presented in this work is powered by a novel hierarchical probabilistic artificial neural network that works along with the knowledgebase of novel benchmark database of digitized cervical cells. The primary purpose of employing expert systems in medicine is creation of such artificially intelligent systems which can provide assistance to a medical doctor in delivering expert diagnosis. These artificial intelligent systems support the clinical decision making by anticipating the diagnostic results once they are trained using previously acquired training data. The use of Artificial intelligence in medicine has shown substantial progress in achieving timely, reliable diagnosis and more precise treatment of many diseases.The expert system developed in this work exhibited a competence of about 92% which has been evaluated by comparing its results with the identification & classification of cervical cells by human experts. Abid Sarwar"Cervical Smear Analyzer (CSA) Expert System for identification of cervical cells in Papanicolaou smear test" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7047.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/7047/cervical-smear-analyzer-csa-expert-system-for-identification-of-cervical-cells-in-papanicolaou-smear-test/abid-sarwar

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