Preterm births account for almost 1 million deaths globally. The objective of this study is to develop and evaluate a model that assists clinicians in assessing the risk of preterm birth, using fuzzy multicriteria analysis. The model allows experts to incorporate their intuition and judgment into the decision-making process and takes into consideration six (6) risk dimensions reflecting the socio-economic, behavioural and medical profile of pregnant women, thus adopting a holistic approach to risk assessment. Each risk dimension is further analysed and measured in terms of risk factors associated with it. Data was collected from a selected group of 35 experts, each one with more than 20 years of obstetric experience. The model criteria were selected after a thorough literature analysis, so as to ensure a holistic approach to risk assessment. The criteria were reviewed by the experts and the model structure was finalised. The fuzzy analytic hierarchy method was applied to calculate the relative importance of each criterion and subsequent use of the model in assessing and ranking pregnant women by their preterm risk. The proposed model utilises fuzzy logic and multicriteria analysis. It addresses the multifactorial nature of decision making when assessing the preterm birth risk. It also incorporates the obstetricians' intuitive judgement during risk assessment and it can be used to classify cases based upon their risk level. Additionally, it can be applied to evaluate the risk of individual cases in a personalised manner. The proposed model is compared and validated for its predictive value against judgments made by experts.

中文翻译：

---

使用模糊层次分析法构建和验证早产风险评估模型。

早产在全球造成近 100 万人死亡。本研究的目的是开发和评估一个模型，该模型可帮助临床医生使用模糊多标准分析评估早产风险。该模型允许专家将他们的直觉和判断纳入决策过程，并考虑到反映孕妇社会经济、行为和医疗状况的六 (6) 个风险维度，从而采用整体方法进行风险评估。每个风险维度都根据与其相关的风险因素进行进一步分析和衡量。数据是从选定的 35 名专家组中收集的，每位专家都有超过 20 年的产科经验。模型标准是在彻底的文献分析后选择的，以确保风险评估的整体方法。专家审查了标准，并最终确定了模型结构。应用模糊层次分析法计算每个标准的相对重要性，并随后使用该模型按早产风险对孕妇进行评估和排名。所提出的模型利用模糊逻辑和多标准分析。它解决了评估早产风险时决策的多因素性质。它还结合了产科医生在风险评估过程中的直观判断，可用于根据风险等级对病例进行分类。此外，它还可以用于以个性化的方式评估个别案例的风险。所提出的模型与专家的判断进行比较和验证其预测价值。