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. 2026 Feb 2;13:1744053. doi: 10.3389/fvets.2026.1744053

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Copyright © 2026 Abdelrahman, Issa, Elsayed Ali, Alotaibi and Alshanbari.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Flowchart illustrating the machine learning lifecycle in eleven steps: 1) Problem Definition, 2) Data Collection, 3) Data Preprocessing, 4) Feature Selection, 5) Model Selection, 6) Training, 7) Validation, 8) Testing, 9) Evaluation, 10) Deployment, 11) Monitoring and Maintenance. Each step includes brief descriptions to guide the process from initial problem identification to continuous model monitoring. — Describes initiating a machine learning model.