A design and development of support system for prediction of various renal syndromes using artificial neural networks

Abstract

The core intention of this theory is prognosis of differential renal syndromes and prediction of nephrolithiasis utilizing Artificial Neural Networks (ANN). An Artificial Neural Network (ANN) is an information processing paradigm that is propelled similar to the natural sensory organs, such as the brain, nerves that process, exchange and stores the data. This system is produced to support the medical specialist in their determination by enabling them to less utilization of time in recognizing small imperfections in the Renal system. It is fundamental to remind that this product does not affirm to supplant the physician, as expert evaluation assessment is regularly essential, particularly in new cases. The key component of this proposed pattern is the new structure of the information processing system. Neural networks, because of its striking capacity to obtain unpredictable or uncertain information, is applied to extract patterns and perceive trends that, are too hard to handle to the human beings or other computer techniques [Kevin J Am Soc Nephrol, 2019]. The developed and trained neural network is considered as an “expert” in the class of information that is provided to analyze. This expert system then can be used to afford projections given new patterns. Neural networks are widely used in the areas like character recognition, image compression, stock market prediction, travelling sale’s man problem; security based miscellaneous and medical applications. In other words the conventional technique for the human subjective assessment strategy is being substituted by computer based systems utilizing soft computing approaches [Am Soc Nephrol, 2019]. Presently neural networks are widely utilized as a part of medical fields so that the proposed system is designed, constructed and developed for diagnosis of differential renal syndromes that acts as most excellent support for the therapeutic professionals [Xie Kidney Dis, 2020][Dayyal Bioscience, 2018]. As there is brisk increase in population the need of more nephrologists is vital. To reach the demand the proposed system is developed to support the medical practitioners [Shahid PLOS ONE, 2019]. The proposed system not only supports the medical practitioners in giving accurate results but also reduces the time and cost.