國立臺北大學統計學系

專題演講

 

講題： Machine Learning to Advance Genome-Wide Association Studies for Predicting Progression of Pediatric Asthma

主講人：張書瑋 教授 (長庚大學健康數據科學研究所)

時間：114年12月3日 (星期三，13：10~15：00)

地點：三峽校區商學院3F13教室

Abstract

Due to the challenges in diagnosing the progression of pediatric asthma, persistence, exacerbation, and rehabilitation in particular, we developed a predictive framework that integrated whole-genome genotyping data with questionnaire and clinical information to classify disease outcomes. Through multiple combinations of different feature screening methods, sampling strategies, and machine learning and deep learning models, we successfully applied high-dimensional genotyping data to model training. Approxiately 6.27 million SNP features in the original data were reduced to a couple of hundreds to less than two thousand, which still achieved excellent predictive performance (ROC AUC from 0.95 to 0.98). We also integrated the results of all training combinations to compare the performance of different models to identify the key predictive features of the best model. The machine learning model we trained was proved to effectively predict the occurrence and persistence of asthma in children.

 

~歡迎參加~

國立臺北大學統計學系  敬邀

114.11.26

附件：演講摘要