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Discovered Facts Related to Liver Cancer Diagnosis – A Research Perspective
Author(s) -
Manish Tiwari,
Prąsun Chakrabarti
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016908044
Subject(s) - computer science , perspective (graphical) , liver cancer , data science , cancer , artificial intelligence , medicine
authors have proposed some discovered facts related to liver cancer diagnosis .The analysis of intensity of liver cancer growth can be governed by artificial neural modeling. The progress of treatment of liver cancer based on past event (intensities of cancer growth at specific observed timing instants) can be computed on the basis of neuro-associator. The augmentation or expansion of features indicating liver cancer growth can be quantified and realized based on Markov property based state transition. The investigation related to liver cancer detection can be governed by the fundamental concept of geometric distribution. The investigation related to significance of parameters responsible for liver cancer can be realized in the light of the Cobb- Douglas model. Liver cancer detection can be realized based upon the fundamental principle of information gain. The reliability and mean time to failure of liver cancer testing system can be realized in the light of parallel system configuration. The effect of alcohol consumption leading to liver cancer can be sensed using the concept learning approach. Keywords-associator, Markov property based transition, Cobb- Douglas model, information gain, reliability, concept learning.

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