Affiliated People's Hospital of Jiangsu University, 8 Dianli Road, Zhenjiang, Jiangsu, 212000, China.
The First Clinical College, Wenzhou Medical University, Wenzhou, 325000, China.
Comput Biol Med. 2022 Jul;146:105529. doi: 10.1016/j.compbiomed.2022.105529. Epub 2022 Apr 18.
Pulmonary hypertension (PH) is a rare and fatal condition that leads to right heart failure and death. The pathophysiology of PH and potential therapeutic approaches are yet unknown. PH animal models' development and proper evaluation are critical to PH research. This work presents an effective analysis technology for PH from arterial blood gas analysis utilizing an evolutionary kernel extreme learning machine with multiple strategies integrated slime mould algorithm (MSSMA). In MSSMA, two efficient bee-foraging learning operators are added to the original slime mould algorithm, ensuring a suitable trade-off between intensity and diversity. The proposed MSSMA is evaluated on thirty IEEE benchmarks and the statistical results show that the search performance of the MSSMA is significantly improved. The MSSMA is utilised to develop a kernel extreme learning machine (MSSMA-KELM) on PH from arterial blood gas analysis. Comprehensively, the proposed MSSMA-KELM can be used as an effective analysis technology for PH from arterial Blood gas analysis with an accuracy of 93.31%, Matthews coefficient of 90.13%, Sensitivity of 91.12%, and Specificity of 90.73%. MSSMA-KELM can be treated as an effective approach for evaluating mouse PH models.
肺动脉高压（PH）是一种罕见且致命的疾病，可导致右心衰竭和死亡。PH 的病理生理学和潜在的治疗方法尚不清楚。PH 动物模型的开发和正确评估对 PH 研究至关重要。本工作利用具有多种策略集成粘菌算法（MSSMA）的进化核极端学习机，从动脉血气分析中提出一种有效的 PH 分析技术。在 MSSMA 中，向原始粘菌算法中添加了两个有效的蜜蜂觅食学习操作符，以确保强度和多样性之间的适当折衷。在三十个 IEEE 基准测试上评估了所提出的 MSSMA，统计结果表明，MSSMA 的搜索性能得到了显著提高。利用 MSSMA 开发了一种用于动脉血气分析 PH 的核极端学习机（MSSMA-KELM）。总之，所提出的 MSSMA-KELM 可以作为一种有效的动脉血气分析 PH 分析技术，其准确率为 93.31%，马修斯相关系数为 90.13%，灵敏度为 91.12%，特异性为 90.73%。MSSMA-KELM 可作为评估小鼠 PH 模型的有效方法。
