Healthc Inform Res.  2022 Jul;28(3):267-275. 10.4258/hir.2022.28.3.267.

Modification of Case-Based Reasoning Similarity Formula to Enhance the Performance of Smart System in Handling the Complaints of in vitro Fertilization Program Patients

Affiliations
  • 1Department of Computer Science, Satya Wacana Christian University, Salatiga, Indonesia
  • 2College of Informatics and Computer Management (STMIK), Widya Pratama, Pekalongan, Indonesia

Abstract


Objectives
Eighty percent of in vitro fertilization (IVF) patients have high anxiety levels, which influence the success of IVF and drive IVF patients to quickly report any abnormal symptoms. Rapid responses from fertility subspecialist doctors may reduce patients’ anxiety levels, but fertility subspecialist doctors’ high workload and their patients’ worsening health conditions make them unable to handle IVF patients’ complaints quickly. Research suggests that smart systems using case-based reasoning (CBR) can help doctors handle patients quickly. However, a prior study reported enhanced accuracy by modifying the CBR similarity formula based on Lin’s similarity theory to generate the Chris case-based reasoning (CCBR) similarity formula.
Methods
The data were validated through interviews with two fertility subspecialist doctors, interviews with two IVF patients, a questionnaire administered to 17 community members, the relevant literature, and 256 records with data on IVF patients’ complaints and how they were handled. An experiment compared the performance of the CBR similarity formula algorithm with the CCBR similarity formula algorithm.
Results
A confusion matrix showed that the CCBR similarity formula had an accuracy value of 52.58% and a precision value of 100%. Fertility subspecialist doctors stated that 89.69% of the CCBR similarity formula recommendations were accurate.
Conclusions
We recommend applying a combination of the CCBR similarity formula and a minimum reference value of 80% with a CBR smart system for handling IVF patients’ complaints. This recommendation for an accurate system produced by the CBR similarity formula may help fertility subspecialist doctors handle IVF patients’ complaints.

Keyword

Anxiety; Complaint; Doctors; Fertility; Patients

Figure

  • Figure 1 Research stages. IVF: in vitro fertilization, CBR: case-based reasoning, CCBR: Chris case-based reasoning.

  • Figure 2 Algorithms of the CBR similarity formula and the CCBR similarity formula. CBR: case-based reasoning, CCBR: Chris case-based reasoning.

  • Figure 3 CBR system flow. IVF: in vitro fertilization, CBR: casebased reasoning, CCBR: Chris case-based reasoning.

  • Figure 4 Similarity values. CBR: casebased reasoning, CCBR: Chris case-based reasoning.

  • Figure 5 Comparison between accuracy and precision values. CBR: case-based reasoning, CCBR: Chris case-based reasoning.


Reference

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