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A Chatbot with Artificial Intelligence that Uses Natural Language Processing and Noval Deep Reinforcement Learning to Predict Medical Symptoms
0
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5
Autoren
2025
Jahr
Abstract
Goal: The goal is to use Python to build a chatbot—an artificial conversational entity—that can anticipate pharmaceutical dosages for medical procedures. Materials and Procedures: Two methods Sample sizes for deep reinforcement and deep learning algorithms are compared, with sample sizes chosen from 28. G power of 80%, and sample sizes computed using the G power tool. Findings and Discussion: When compared to deep learning, which has an accuracy of 85%, the score model’s performances confirmed the test set accuracy with a 95% confidence interval for the Deep Reinforcement algorithm with varying subsamples having varying numbers of intents. Conclusion: Based on the data, it can be said that the suggested method, Deep Reinforcement, will outperform the current algorithm.
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