Abstract Background Intestinal parasitic infections can harm health by causing malnutrition, anemia, impaired growth and cognitive development, and alterations in microbiota composition and immune responses. Therefore, it is crucial to examine stool samples to diagnose parasitic infections. However, the traditional microscopic detection method is time-consuming, labor-intensive, and dependent on the expertise and training of microscopists. Hence, there is a need for a low-complexity, high-throughput, and cost-effective alternative to labor-intensive microscopic examinations. Methods This study aimed to compare the performance of a fully automatic digital feces analyzer, Orienter Model FA280 (People’s Republic of China) with that of the formalin-ethyl acetate concentration technique (FECT). We assessed and compared the agreement between the FA280 and the FECT for parasite detection and species identification in stool samples. The first part of the study analyzed 200 fresh stool samples for parasite detection using the FECT and FA280. With the FA280, the automatic feces analyzer performed the testing, and the digital microscope images were uploaded and automatically evaluated using an artificial intelligence (AI) program. Additionally, a skilled medical technologist conducted a user audit of the FA280 findings. The second set of samples comprised 800 preserved stool samples (preserved in 10% formalin). These samples were examined for parasites using the FECT and FA280 with a user audit. Results For the first set of stool samples, there was no statistically significant difference in the pairwise agreements between the FECT and the FA280 with a user audit (exact binomial test, P = 1). However, there were statistically significant differences between the pairwise agreements for the FECT and the FA280 with the AI report (McNemar’s test, P
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