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AI FECAL

Fast, reliable data

Delivering expert-level1,2 data to help inform diagnosis and treatment selection

The algorithm and fecal sample preparation techniques on the Vetscan Imagyst® AI Fecal application were vigorously tested in multiple studies.1-4

Algorithm Performance

The algorithm performance of AI Fecal closely matched that of diagnostic parasitology experts.1,2

HOOKWORMS*
(Ancylostoma spp)
ROUNDWORMS*
(Toxocara spp)
WHIPWORMS
(Trichuris vulpis)
TAPEWORMS*
(Taeniidae)
COCCIDIA*
(Cystoisospora spp)
GIARDIA*
Sensitivity
(95% CI)
90.7%
(86.4-94%)
95.5%
(91.7-97.8%)
93.1%
(87.8-96.5%)
100%
(78.3-100%)
94.9%
(90.6-97.6%)
92.1%
(83.5-96.9%)
Specificity
(95% CI)
97.5%
(95.8-98.6%)
98.3%
(96.9-99.2%)
99.7%
(98.7-100%)
97.8%
(93.1-99.5%)
96%
(94.1-97.4%)
98.8%
(94.6-99.9%)

95% Jeffreys confidence interval

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Bringing specialist-level medicine to your clinic

The Zoetis Virtual Laboratory is an integrated support network of board-certified specialists paired with expert-level AI5-12, providing actionable insights to help you diagnose and treat with confidence.

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    Customer Service, Support & Ordering

    Mon – Fri: 8:30am – 6:30pm ET

    Vetscan and i-STAT Technical Support

    24 hours a day, 7 days a week, 365 days a year

    1-888-963-8471

    Zoetis Reference Laboratories Customer Service, Support & Ordering

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    Sunday: Closed

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    Need Technical Support?

    Our support team is available to answer product questions and provide guidance.§

  • * Dog and cat samples combined.

    Dog samples only. Trichuris ova not seen in feline samples.

    Dependent on consultant availability.

    § If you are a pet owner looking for treatment recommendations, please contact your veterinarian.

    References: 1. Nagamori Y, Scimeca R, Hall-Sedlak R, et al. Multicenter evaluation of the Vetscan Imagyst system using Ocus 40 and EasyScan One scanners to detect gastrointestinal parasites in feces of dogs and cats. Journal of Veterinary Diagnostic Investigation. 2023;0(0). doi:10.1177/10406387231216185 2. Data on file, Study No. D860R-US-19-078, Zoetis Inc. 3. Nagamori Y, Sedlak RH, DeRosa A, et al. Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm. Parasites Vectors 14, 89 (2021). 13(1):346. doi:10.1186/ s13071-020-04215-x. 4. Nagamori Y, Hall Sedlak R, DeRosa A, et al. Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm. Parasites Vectors 13, 346 (2020). 5. Data on file, Study No. DHX6Z-US-23-205, 2024, Zoetis Inc. 6. Data on file, Study No. DHX6Z-US-23-206, 2024, Zoetis Inc. 7. Data on file, Study No. DHX6Z-US-23-209, 2024, Zoetis Inc. 8. Nagamori Y, Hall-Sedlak R, Blagburn B, et al. Multicenter evaluation of the Vetscan Imagyst system using Ocus 40 and EasyScan One scanners to detect gastrointestinal parasites of feces in dogs and cats. Journal of Veterinary Diagnostic Investigation. 2023;36(1). doi: 10.1177/10406387231216185. 9. Data on file, Study No. DHXMZ-US-23-218, 2023, Zoetis Inc. 10. Data on file, Study No. DHX6Z-US-23-222, 2023, Zoetis Inc. 11. Data on file, Study No. DHX6Z-US-22-131, 2022, Zoetis Inc. 12. Data on file. Study No. DHXMZ-US-24-235, 2024, Zoetis Inc.

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