Overcoming Ambiguity: Delve Into the Ignition of the Explainable AI Field to Develop Human-Understandable Systems & Enhance Interpretability
Time: 1:30 pm
day: Pre-Conference Day
Details:
AI models used in drug discovery often operate as black boxes, making it difficult for researchers to understand how they arrive at specific predictions or recommendations. Interpretability and explainability are crucial, especially in drug development, as stakeholders need to understand the underlying reasoning behind AI-driven decisions to trust the models’ predictions and make informed decisions about candidate compounds. Developing AI models that are both accurate and interpretable remains a significant challenge.
This workshop will gather experts to discuss
- Accelerating towards the development of AI models with explainable mechanisms to augment their transparency in early drug discovery research and enable researchers to make informed decisions
- Delving into AI-DDIs studies, methods used in data manipulation and feature pre-processing
