專題演講 主講人:魏裕中教授(彰化師範大學統計資訊研究所)

  • 事件日期: 2022-09-30
  • 演講者:  /  主持人:
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題 目:A Tree-based Explainable Artificial Intelligence Algorithm to Evaluate the Effect of

Genetic Variants on Phenotype

主講人:魏裕中教授(彰化師範大學統計資訊研究所)

時 間:111年9月30日(星期五)上午10:40-11:30
(上午10:20-10:40茶會於交大統計所428室舉行) 

地 點:綜合一館427室

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摘要
 
Next-generation sequencing enables efficient detection of various types of genetic variants and then assesses their association with phenotypes. Although a massive of machine learning methods have been developed, most of these algorithms just focus on high accuracy instead of interpretability. The lack of interpretability makes the machine learning methods hard to apply to medical and genetic issues. In this research, an explainable artificial intelligence (also known as interpretable machine learning) algorithm was proposed. A tree-based predictive model with the Bayesian model combination strategy was used to predict phenotype from genetic variants. The post-hoc explanative model was used to display the importance of phenotype-relevant genetic variants and their interactions. The proposed algorithm was applied to evaluate the effect of genetic variants on severe insulin resistance patients in the UK10K dataset.

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