<p>This paper investigates the application of AI (Artificial Intelligence) in the exploration of intestinal parasitic eggs, especially the feature extraction, detection, segmentation, and classification of parasitic egg images. The paper performs a systematized review to determine critical research questions about how AI trends improve these processes. A careful search of highly recognized digital libraries follows an exact appraisal of papers for relevant inclusion or exclusion. Multiple studies yield significant improvements in AI-based techniques that perform feature extraction and detection and classification operations. A close evaluation of precision, recall and F1 scores existing between research conducted by couple of researches focuses on parasitic egg classification results. Nevertheless, challenges such as data quality and quantity, computational resources, real-time analysis, and cost remain important considerations in the application of AI for parasitic egg analysis. This paper demonstrates substantial understanding of contemporary AI-based intestinal parasitic egg analysis that will support upcoming research and development activities the field.</p>