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Diagnose and Treat Cancer Patients using Rule-Based/Fact-Based Artificial Intelligence Techniques.

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"Philosophy ought to imitate the successful sciences in its methods, so far as to proceed only from tangible premisses which can be subjected to careful scrutiny, and to trust rather to the multitude and variety of its arguments than to the conclusiveness of any one. Its reasoning should not form a chain which is no stronger than its weakest link, but a cable whose fibres may be ever so slender, provided they are sufficiently numerous and intimately connected."
( "Some Consequences of Four Incapacities", Charles S. Peirce )

I used to always say, "We live in the best time because, with computers, we have the world at our fingertips."

While I still believe that is very true, I now give a more accurate depiction instead:

"We live in the best time because we have infinite knowledge at our fingertips."

My goal is to develop this ai model in a way that i can implement other types of queries such as advice referencing any material e.g. cancer diagnosis, treatments, documentation/researches, animal diagnosis/treatments, The Holy Bible references, and so much more.

Humans are active participants in knowledge-making. And our dynamic and interactive inquiries based on experience provides us our knowledge which is what adds to our rule set and fact set. I am developing a fact/rule based artificial intelligence program which uses a knowledge base. Over time, I will develop the knowledge base to be trained based on inquiries from deep learning algorithms as well as developer-set rules.

“In rule-based AI, the fact base provides input, the rule base processes it, and the knowledge base contains all necessary relationships.”

Table of Contents

ruleBase
knowledgeBase creates rules using facts (will use a Rule Base and and a Fact Base)

forwardChaining
backwardChaining

Data Structure Differences Rule Based Intelligent Expert System Configuration

Base-Matrix

Driver flow

Flowchart

Rules

Rules

Backward Chaining

flowchart-backwardChaining

Testing backwardChaining::userValidClauseVect and backwardChaining::generateSubsets

test-backwardChaining-userValidClauseVect

Testing backwardChaining.cpp's Determination of Possible Conclusions

possibleSolution

Testing backwardChaining.cpp's Diagnosis

diagnosis

Testing decisionTree.h

dt

Testing treeTypes.h

Each Conclusion inherits and overrides a Global Static Decision Tree for polymorphic capabilities:

treeTypes

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Diagnose and Treat Cancer Patients using Rule-Based/Fact-Based Artificial Intelligence Techniques.

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