Toward Trustworthy Machine Learning to Understand the Genetic Basis of Phenotyped Subtypes of Alzheimer’s disease

Seminar Date: 
2021-12-10
Seminar Time: 
11am - 12pm
Seminar Location: 
5607 Baum Boulevard, Room 407A
Presenter: 
Haohan Wang, PhD
Presenter's Institution: 
Carnegie Melloin University

The development of machine learning techniques has offered us a new opportunity to analyze complex structured neuroscience data at a large scale to unveil the pathology of some neurodegenerative disorders and to offer potential preventive and therapeutic strategies. However, a plain application of machine learning methods, especially the black-box-nature deep learning techniques developed in recent years, may result in plausible knowledge discovered through the model’s learning of spurious features or confounding factors, such as aging factors or batch effects. Therefore, the development of machine learning tools that can incorporate the knowledge of neuroscientists and geneticists to consider the data heterogeneity nature and counter the data idiosyncrasy confounding factors is of great importance.

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