【摘要】 卵巢储备功能与反应性密切相关，其评估是辅助生殖技术中控制性卵巢刺激的前提。评估卵巢储备功能和反应性的指标包括：年龄、生化指标、超声检查窦状卵泡计数等，上述指标既可单独应用又可联合应用评估卵巢储备功能和反应性。目前，人工智能技术通过整合多模态数据来优化卵巢储备功能和反应性的评估与预测，弥补传统评估方法的局限性，展示出良好的应用前景。更多还原

【Abstract】 Ovarian reserve function is closely associated with ovarian responsiveness,and its assessment is a prerequisite for controlled ovarian stimulation in assisted reproductive technology. Indicators for evaluating ovarian reserve and responsiveness include age,biochemical indicators,and ultrasound-measured antral follicle count(AFC),etc. These indicators can be used either individually or in combination to assess ovarian reserve and responsiveness. Currently,artificial intelligence(AI)technology is used to optimize the evaluation and prediction of ovarian reserve and responsiveness by integrating multimodal data, compensating for the limitations of traditional assessment methods and demonstrating promising application prospects.更多还原