乳腺癌新辅助疗效临床辅助决策模型

该模型是基于人工智能深度学习方法研究的创新性模型，可实现对乳腺癌患者新辅助治疗前、后“两阶段多序列”MRI影像中乳腺癌病灶区域的自动化识别、特征抽取和临床数据结合，最终实现乳腺癌患者治疗效果的智能评估，为临床决策提供有效参考和辅助依据，为医疗机构精准医疗目标赋能。

This innovative model is developed based on artificial intelligence and deep learning methodologies. It is capable of automated detection and feature extraction of breast cancer lesion regions in "two-stage multi-sequence" MRI images acquired before and after neoadjuvant therapy for breast cancer patients, and integrates such analyses with clinical patient data. Ultimately, it realizes intelligent evaluation of the treatment efficacy of breast cancer patients, providing effective references and auxiliary supports for clinical decision-making, and empowering medical institutions to advance their precision medicine objectives.