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Development and validation of Semen Interpreter, a mobile application-based point-of-care guidance tool for the evaluation of Male Factor Infertility Pankaj Shinde , Pooja Shukla, Arti Singh, Yuthika Sharma. From 1 Department of Obstetrics & Gynecology and 2 Department of Reproductive Medicine, Regency Healthcare, Kanpur, Background: Semen analysis is pivotal to the evolution of the male factor infertility. Erroneous interpretation of semen analysis has significant short and long-term implications. This makes developing a point-of-care tool for semen analysis interpretation desirable. Traditional methods demand time, expertise, and manual effort from specialists. The app-based semen interpreter analyzes semen using assistants, saving time without compromising accuracy or quality. Objective: To develop and validate a point-of-care mobile application to guide the interpretation of Semen Analysis. Methods: We developed the Semen interpreter, a mobile application-based tool that provides algorithmic guidance for interpreting semen analysis. The interpreter guidance was validated against a senior gynecologist, reproductive medicine fellow, and gynecology trainee in 100 couples who presented to our Reproductive medicine unit from April 2024 to October 2024. All semen analyses were performed in-house as per the 2008 WHO guidelines. The interpretation provided by the clinicians and the Semen Interpreter was compared to the gold standard interpretation of our unit's Senior Reproductive Medicine specialist. Results: The concordance score for Semen interpreter (96%) and Senior Gynecologist (84%) was greater than that for reproductive medicine fellow (72%) and gynecology trainee (64%). Common errors by gynecology trainees included inaccurate interpretation of motile sperm concentration and subsequent advice. Conclusion: The findings of our study confirm the accuracy of Semen interpreters in guiding the evaluation of male partners in couples with infertility. The widespread availability of a simple tool accessible offline is expected to allow for early and correct diagnosis. There is a need for multicentric validation before widespread use.