<![CDATA[Preeclampsia is a leading cause of maternal and fetaldeath. Early detection of the risk of preeclampsia isessential. This study aims to analyze the application of theCertainty Factor method in an expert system for earlydetection of preeclampsia risk, identify preeclampsiasymptoms based on trimester of pregnancy, and developrecommendations for developing a knowledge base thatmatches the characteristics of preeclampsia symptoms. Thestudy used a literature review method through articlesearches in the Scopus and Google Scholar databases, aselection process based on inclusion and exclusion criteria,extraction, descriptive analysis, and synthesis of eligiblearticles. The analysis focused on the application of theCertainty Factor method, knowledge sources, symptomsused, inference techniques, diagnostic results, and thecharacteristics of preeclampsia symptoms in each trimesterof pregnancy. The results show that the Certainty Factormethod has been widely applied in expert systems tosupport early detection of preeclampsia and otherpregnancy-related diseases through rule-based reasoningand diagnostic confidence level calculations. Research stilluses a static knowledge base without considering changesin symptom characteristics according to gestational age. Itis proposed that the development of a knowledge basestructured by trimester of pregnancy aims to improveinference accuracy and reduce misinterpretation ofsymptoms.]]>
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