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BEGIN:VEVENT
DTSTAMP:20261005T141013Z
UID:7321e88e-0a98-48d1-bc11-cda722b1b2e6
DTSTART:20261023T070000Z
DTEND:20261023T150000Z
DESCRIPTION:Artificial intelligence is inspiring potential new applications
  across the life sciences – from diagnosing disease in medical images to
  predicting clinical outcomes from tabular health records. But as AI model
 s grow more powerful\, they also grow more opaque. In high-stakes domains 
 such as life sciences and healthcare\, a prediction alone is not enough: w
 e need to understand why a model made it\, whether it can be trusted\, and
  whether it learned the right thing or a shortcut.\n\nIn this workshop\, w
 e will give an introduction to explainable AI (xAI) and its role in the li
 fe sciences. Through interactive lectures and hands-on notebooks\, partici
 pants will apply explanation methods such as SHAP\, feature importance\, s
 aliency maps\, and Grad-CAM to real medical datasets – including brain s
 troke prediction from tabular data and classification of chest X-ray image
 s. By the end of the workshop\, you will have hands-on experience in gener
 ating\, interpreting\, and critically validating AI explanations on real-l
 ife science problems
SUMMARY:Explainable AI for Life Science
URL;VALUE=URI:https://swedenaifactory.se/event/explainable-ai-for-life-scie
 nce/
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