Pulmonary Hypertension(PH)is a global health problem that affects about 1%of the global population.Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease.The present study...Pulmonary Hypertension(PH)is a global health problem that affects about 1%of the global population.Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease.The present study proposes a Kernel Extreme Learning Machine(KELM)model based on an improved Whale Optimization Algorithm(WOA)for predicting PH mouse models.The experimental results showed that the selected blood indicators,including Haemoglobin(HGB),Hematocrit(HCT),Mean,Platelet Volume(MPV),Platelet distribution width(PDW),and Platelet–Large Cell Ratio(P-LCR),were essential for identifying PH mouse models using the feature selection method proposed in this paper.Remarkably,the method achieved 100.0%accuracy and 100.0%specificity in classification,demonstrating that our method has great potential to be used for evaluating and identifying mouse PH models.展开更多
基金the National Natural Science Foundation of China(82003831,62076185 and U1809209)the Project of Health Commission of Zhejiang Province(2020KY177)+2 种基金the Wenzhou Technology Foundation(Y2020002)the Natural Science Foundation of Zhejiang Province(LZ22F020005)the First Affiliated Hospital of Wenzhou Medical University Youth Excellence Project(QNYC114).
文摘Pulmonary Hypertension(PH)is a global health problem that affects about 1%of the global population.Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease.The present study proposes a Kernel Extreme Learning Machine(KELM)model based on an improved Whale Optimization Algorithm(WOA)for predicting PH mouse models.The experimental results showed that the selected blood indicators,including Haemoglobin(HGB),Hematocrit(HCT),Mean,Platelet Volume(MPV),Platelet distribution width(PDW),and Platelet–Large Cell Ratio(P-LCR),were essential for identifying PH mouse models using the feature selection method proposed in this paper.Remarkably,the method achieved 100.0%accuracy and 100.0%specificity in classification,demonstrating that our method has great potential to be used for evaluating and identifying mouse PH models.
