AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is suggested that selected panoramic observations may provide supplementary information during case assessment, but should not be interpreted as standalone predictive criteria for estimating spontaneous space closure in children requiring P1M extraction.
While XGBoost yielded the highest overall classification accuracy, ChatGPT-5.0's high sensitivity in detecting extraction cases was noteworthy, and it demonstrated performance comparable to, and in some cases superior to, traditional ML models for orthodontic extraction decisions.
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