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Program Description:
A urinalysis is an essential component of the minimum database, but it is often not performed for numerous reasons. It is important to understand the barriers to urinalyses being performed in order to propose productive solutions that will ensure best medicine for our patients. In addition, there may be a lack of standardization within urine sediment examinations leading to variability in results. This podcast will highlight current concerns around urine sediment analysis and discuss upcoming solutions to workflow efficiency and result consistency.

Program Agenda:

• Review the justification for a urinalysis being an essential component of a minimum database along with the current recommendations for performing a urinalysis as part of diagnostic health screenings.
• Present current compliance towards performing a urinalysis within veterinary practice and what factors lead to its exclusion from a minimum database.
• Discuss the segments of the urinalysis workflow that introduce potential error or imprecisions.
• Introduce Artificial Intelligence and Differentiate Superficial vs Deep Learning AI.
• Introduce potential solutions to overcome workflow and standardization concerns.

Learning Objectives: * List clinical instances in which a urinalysis would be performed. * Understand current barriers to more frequent use of the urinalysis in veterinary hospitals. * Evaluate potential sources of error or lack of standardization in urinalysis workflow and results within the veterinary hospital. * Recognize the differences between various types of artificial intelligence and understand how deep learning artificial intelligence can advance the accuracy of urine sediment evaluation.