Evolution of technology has brought a revolution in various fields of sciences and amongst them, healthcare is one of the most critical and sensitive areas because of its connection with common masses' quality of life. The notion of integrating the healthcare system with the latest data repositories is to make disease prediction efficient, transparent, and reusable. Due to data heterogeneity, data repositories along with optimum classifiers help stakeholders to predict the disease more accurately without compromising the interpretability. Evolutionary algorithms have shown great efficacy, accuracy, and interpretability in improving disease prediction for several datasets. However, the quest for the best classifier is still in evolution. In this research, a state-of-the-art medical data repository has been developed to give researchers of medical domain great ease of use in utilizing different datasets governed by a multi-objective evolutionary algorithm using fuzzy genetics. The proposed model called ‘MEAF’ is evaluated on various public repositories. A subset of these repositories includes breast cancer, heart, diabetes, liver, and hepatitis datasets. The results have been analyzed, which show competitive accuracy, sensitivity, and interpretability as compared to relevant research. A customised software application named ‘MediHealth’ is developed to supplement the proposed model that will facilitate the domain users.

中文翻译：

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使用健康数据存储库开发临床系统软件：多目标模糊遗传方法

技术的发展在科学的各个领域带来了一场革命，其中，医疗保健是最关键和最敏感的领域之一，因为它与普通大众的生活质量息息相关。将医疗保健系统与最新数据存储库集成的想法是使疾病预测高效，透明和可重用。由于数据的异构性，数据存储库以及最佳分类器可帮助利益相关者更准确地预测疾病，而不会影响可解释性。进化算法在改善几个数据集的疾病预测方面显示出巨大的功效，准确性和可解释性。但是，对最佳分类器的追求仍在发展中。在这项研究中 已经开发了最先进的医学数据存储库，以使医学领域的研究人员在使用由模糊遗传多目标进化算法控制的不同数据集时，具有极大的易用性。建议的模型“ MEAF”在各种公共存储库中进行了评估。这些存储库的子集包括乳腺癌，心脏病，糖尿病，肝和肝炎数据集。对结果进行了分析，与相关研究相比，它们显示出竞争准确性，敏感性和可解释性。开发了名为“ MediHealth”的定制软件应用程序，以补充建议的模型，该模型将方便域用户。建议的模型“ MEAF”在各种公共存储库中进行了评估。这些存储库的子集包括乳腺癌，心脏病，糖尿病，肝和肝炎数据集。对结果进行了分析，与相关研究相比，它们显示出竞争准确性，敏感性和可解释性。开发了名为“ MediHealth”的定制软件应用程序，以补充建议的模型，该模型将方便域用户。建议的模型“ MEAF”在各种公共存储库中进行了评估。这些存储库的子集包括乳腺癌，心脏病，糖尿病，肝和肝炎数据集。对结果进行了分析，与相关研究相比，它们显示出竞争准确性，敏感性和可解释性。开发了名为“ MediHealth”的定制软件应用程序，以补充建议的模型，该模型将方便域用户。