Abstract：
Tuberculous pleural effusion poses a significant threat to human health due to its potential for severe disease and mortality. Without timely treatment, it may lead to fatal consequences. Therefore, early identification and prompt treatment are crucial for preventing problems such as chronic lung disease, respiratory failure, and death. This study proposes an enhanced differential evolution algorithm based on colony predation and dispersed foraging strategies. A series of experiments conducted on the IEEE CEC 2017 competition dataset validated the global optimization capability of the method. Additionally, a binary version of the algorithm is introduced to assess the algorithm\'s ability to address feature selection problems. Comprehensive comparisons of the effectiveness of the proposed algorithm with 8 similar algorithms were conducted using public datasets with feature sizes ranging from 10 to 10,000. Experimental results demonstrate that the proposed method is an effective feature selection approach. Furthermore, a predictive model for tuberculous pleural effusion is established by integrating the proposed algorithm with support vector machines. The performance of the proposed model is validated using clinical records collected from 140 tuberculous pleural effusion patients, totaling 10,780 instances. Experimental results indicate that the proposed model can identify key correlated indicators such as pleural effusion adenosine deaminase, temperature, white blood cell count, and pleural effusion color, aiding in the clinical feature analysis of tuberculous pleural effusion and providing early warning for its treatment and prediction.
摘要：
结核性胸腔积液由于其可能导致严重疾病和死亡，对人类健康构成重大威胁。如果没有及时治疗，这可能会导致致命的后果。因此,早期识别和及时治疗对于预防慢性肺病等问题至关重要，呼吸衰竭,和死亡。本研究提出了一种基于菌落捕食和分散觅食策略的增强型差分进化算法。在IEEECEC2017竞赛数据集上进行的一系列实验验证了该方法的全局优化能力。此外,引入了该算法的二进制版本，以评估该算法解决特征选择问题的能力。使用特征大小从10到10,000的公共数据集，对所提出的算法与8种类似算法的有效性进行了综合比较。实验结果表明，该方法是一种有效的特征选择方法。此外，将提出的算法与支持向量机相结合，建立了结核性胸腔积液的预测模型。使用从140例结核性胸腔积液患者收集的临床记录验证了所提出的模型的性能，总计10780例。实验结果表明,该模型能够识别出胸水腺苷脱氨酶等关键相关指标,温度,白细胞计数,和胸腔积液的颜色，辅助结核性胸腔积液的临床特征分析，为其治疗和预测提供预警。
