ESCBR: Expert System Enabled Case-based Reasoning Approach in iDDCS for CIND

Background: CIN is considered as precancerous stage. If we detect CIN stage in its early manifestation we would be able to avoid cancerous stage. Any gadget with case based reasoning method could improve the accuracy. Objective: Objective of this paper is to combined expert system with CBR. The mycin algorithm base don backward chaining is to be used to identifying CIN and also to compare the afficacy of CBR- Aggregate method with CBR GA and CBR-BSR. Methods: This paper proposes a system consist of two major fundamental component: Expert system and CBR-ES uses mycin algorithm based on backward chaining.and CBR uses CBR aggregate and compare it with CBR-GA and CBR-BSR. Results: The result shows assuring outcome for early CIN detection using both component . The mycin algorithm which uses backward chaining method. Second component CBR aggregate method demonstrated superior performance compared to CBR-GA and CBR-BSR, specially showing a lower frequency of MAPE percentage. Conclusion: The paper concludes that using both Mycin ES and CBR- Aggreate method together for CIN detetction can significantly reduce error rates, leading to timely and proper medical intervention. The simultaneous application of both method for mutual confirmation can greatly enhance the accuracy and reliability of CIN detection.