Poster Open Access

Interpretability for computational biology

Nguyen An-phi; Rodriguez-Martinez

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    <subfield code="a">&lt;p&gt;Why do we need interpretability to unveil the decision process ofa machine learning model?&lt;br&gt;
Trust - for high-risk scenarios, e.g. healthcare, the user needs to trust the decision taken.&lt;br&gt;
Debugging -&amp;nbsp;the model may be badly trained or there might be an unfair bias in either the dataset or the model itself.&lt;br&gt;
Hypothesis generation - surprising results might be consequences of new mechanisms or patterns unknown even to field experts.&lt;/p&gt;</subfield>
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