基于隐马尔科夫模型的胎盘植入产前诊断方法

Prenatal Diagnosis Method of Placenta Accreta Based on Hidden Markov Model

胎盘植入是产科严重的并发症之一,作为金标准的产后病理检验存在的滞后性和局限性问题,文中将病史和彩超数据等产前多特征关联作为观测显状态序列,将产后病理诊断作为隐状态,构建基于隐马尔科夫模型的胎盘植入产前诊断方法.采用Gini方法提取患病关联因素的特征集合,通过转化特征集合构建隐马尔科夫模型,结合Baum-Welch和Viterbi算法计算求解,通过显隐状态关系,实现胎盘植入产前诊断.实验表明,文中方法具有较好的准确率、特异度和灵敏度.

Placenta accreta is one of the most serious complications of obstetrics. As a gold standard, the postnatal pathological examination has hysteresis and limitation. In this paper, the multi-feature associations of medical history information and color Doppler ultrasound data are used as observation sequences and the postpartum pathological results are used as hidden state sequences. The prenatal prediction method of placenta accreta based on hidden Markov model is proposed. The algorithm of Gini is used to extract the disease factors. Then, the hidden Markov model is built by the set of factors. Through the observation and hidden sequences, the prenatal prediction of placenta accreta is accomplished using Baum-Welch and Viterbi algorithms. The experimental results show that the proposed method achieves better diagnostic accuracy, sensitivity and specificity.