{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:34:37Z","timestamp":1740159277384,"version":"3.37.3"},"reference-count":27,"publisher":"The Korean Society of Medical Informatics","issue":"3","license":[{"start":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T00:00:00Z","timestamp":1659225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["e-hir.org"],"crossmark-restriction":true},"short-container-title":["Healthc Inform Res"],"published-print":{"date-parts":[[2022,7,31]]},"abstract":"<jats:p>Objectives: Eighty percent of &lt;i&gt;in vitro&lt;\/i&gt; 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\u2019 anxiety levels, but fertility subspecialist doctors\u2019 high workload and their patients\u2019 worsening health conditions make them unable to handle IVF patients\u2019 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\u2019s 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\u2019 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\u2019 complaints. This recommendation for an accurate system produced by the CBR similarity formula may help fertility subspecialist doctors handle IVF patients\u2019 complaints.<\/jats:p>","DOI":"10.4258\/hir.2022.28.3.267","type":"journal-article","created":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T04:48:44Z","timestamp":1659934124000},"page":"267-275","update-policy":"https:\/\/doi.org\/10.4258\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modification of Case-Based Reasoning Similarity Formula to Enhance the Performance of Smart System in Handling the Complaints of in vitro Fertilization Program Patients"],"prefix":"10.4258","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4518-7433","authenticated-orcid":true,"given":"Paminto 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