Design and Development of a Corpus-Driven Medical English Vocabulary Teaching System

This paper proposes an intelligent medical English teaching system based on dynamic corpus analysis. Through implementing TF-IDF optimization algorithms and LSTM-based learning prediction models, the system achieves <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 3. 6 \%}$</tex> precision in terminology recommendation. The React-based frontend demonstrates sub-second response times under 10,000 concurrent users.