The Statistical Methods for Health Equity Series is a monthly online series co-hosted by the Data Science for Health Equity community, the Alan Turing Institute Health Equity Interest Group, and the Department of Statistical Science at University College London.

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For our next webinar, we're delighted to welcome Nyalleng Moorosi from the Distributed AI Research Institute (DAIR) who will be joining us to explore some discussions around understanding how we can build models which centre populations often regarded as peripheral. Specific details on the topic are as below:

Topic: Documenting Health Datasets - Incentives, Transparency, Audits and Inclusion

Abstract:

Applications of machine learning for health have shown great promise. With the onset of deep learning, especially in computer vision, diagnostic medical fields such as radiology and histology have to contend with algorithms that can perform better than practitioners. In Electronic Health Systems, AI has been used to optimize the allocation of…