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The aim of this research review is to propose the logic and search mechanismfor the development of an artificially intelligent automaton (AIA) that canfind affected cells in a 3-dimensional biological system. Research on thepossible application of such automatons to detect and control cancer cells inthe human body are greatly focused MRI and PET scans finds the affected regionsat the tissue level even as we can find the affected regions at the cellularlevel using the framework. The AIA may be designed to ensure optimumutilization as they record and might control the presence of affected cells ina human body. The proposed models and techniques can be generalized and used inany application where cells are injured or affected by some disease oraccident. The best method to import AIA into the body without surgery orinjection is to insert small pill like automata, carrying material viz drugs orleukocytes that is needed to correct the infection. In this process, the AIAcan be compared to nano pills to deliver or support therapy. NanoHivesimulation software was used to validate the framework of this paper. Theexisting nanomedicine models such as obstacle avoidance algorithm based models(Hla K H S et al 2008) and the framework in this model were tested in differentsimulation based experiments. The existing models such as obstacle avoidancebased models failed in complex environmental conditions (such as changingenvironmental conditions, presence of semi-solid particles, etc) while themodel in this paper executed its framework successfully.Come systems biology,this field of automatons deserves a bigger leap of understanding especiallywhen pharmacogenomics is at its peak. The results also indicate the importanceof artificial intelligence and other computational capabilities in the proposedmodel for the successful detection of affected cells.

Automaton based detection of affected cells in three dimensional biological system