基于知识的体外受精治疗决策支持系统
A Knowledge-Based Decision Support System for In Vitro Fertilization Treatment
摘要：
体外受精（IVF）是目前应用最广泛的辅助生殖技术（ART）。IVF通常包括控制性卵巢刺激、取卵、实验室受精和随后的胚胎移植。前两个步骤对应于女性的卵泡期和月经周期中的排卵。因此，我们在本文中将其称为治疗周期。治疗周期至关重要，因为IVF治疗中的刺激药物直接应用于患者。为了优化刺激效果并降低刺激药物的副作用，需要及时进行治疗调整。此外，获取的卵母细胞的质量和数量对以下程序的结果有显着影响。为了提高试管婴儿的成功率，我们提出了一个基于知识的决策支持系统，可以提供医疗建议的治疗方案和药物调整，为每个病人访问在试管婴儿治疗周期。该系统具有数据处理效率高、重量轻的特点，可以很容易地嵌入到电子病历系统中。此外，面向卵母细胞检索的评估表明，我们的系统在协议和药物建议的准确性方面表现良好。
英文摘要：
In Vitro Fertilization (IVF) is the most widely used Assisted Reproductive Technology (ART). IVF usually involves controlled ovarian stimulation, oocyte retrieval, fertilization in the laboratory with subsequent embryo transfer. The first two steps correspond with follicular phase of females and ovulation in their menstrual cycle. Therefore, we refer to it as the treatment cycle in our paper. The treatment cycle is crucial because the stimulation medications in IVF treatment are applied directly on patients. In order to optimize the stimulation effects and lower the side effects of the stimulation medications, prompt treatment adjustments are in need. In addition, the quality and quantity of the retrieved oocytes have a significant effect on the outcome of the following procedures. To improve the IVF success rate, we propose a knowledge-based decision support system that can provide medical advice on the treatment protocol and medication adjustment for each patient visit during IVF treatment cycle. Our system is efficient in data processing and light-weighted which can be easily embedded into electronic medical record systems. Moreover, an oocyte retrieval oriented evaluation demonstrates that our system performs well in terms of accuracy of advice for the protocols and medications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
