Artificial Intelligence and Responsive Optimization by M. Khoshnevisan, S. Bhattacharya, F. Smarandache

By M. Khoshnevisan, S. Bhattacharya, F. Smarandache

The aim of this booklet is to use the synthetic Intelligence and keep an eye on platforms to various genuine versions. it's been designed for graduate scholars and researchers who're energetic within the purposes of man-made Intelligence and regulate platforms in modeling. In our destiny study, we'll tackle the original points of Neutrosophic common sense in modeling and information research.

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Cancer can form along either route. Contrary to popular belief, cancer cells do not necessarily proliferate faster than the normal ones. Proliferation rates observed in well-differentiated tumors are not significantly higher from those seen in progenitor normal cells. Many normal cells hyperproliferate on occasions but otherwise retain their normal histological behavior. This is known as hyperplasia. In this paper, we propose a non-parametric approach based on an artificial neural network classifier to detect whether a hyperplasic cell proliferation could eventually become carcinogenic.

Non-linear cellular biorhythms and chaos: A major drawback of using a parametric stochastic-likelihood modeling approach is that often closed-form solutions become analytically impossible to obtain. The axiomatic approach involves deriving analytical solutions of stiff stochastic differential-difference equation systems. But these are often hard to extract especially if the governing system is decidedly non-linear like Rubinow’s suggested physiological structure model with 55 velocity v depending on the population density Cn.

Many normal cells hyperproliferate on occasions but otherwise retain their normal histological behavior. This is known as hyperplasia. In this paper, we propose a non-parametric approach based on an artificial neural network classifier to detect whether a hyperplasic cell proliferation could eventually become carcinogenic. That is, our model proposes to determine whether a tumor stays benign or subsequently undergoes metastases and becomes malignant as is rather prone to occur in certain forms of cancer.

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