Special Session on Machine Learning for Drug Discovery
Chair: Lars Carlsson
Machine learning methods are widely used within the pharmaceutical industry. Within biological or chemical applications where machine learning is applied, scientists try to create models of Quantitative Structure-Activity Relationship (QSAR). The modelling is often referred to as QSAR and the problems considered are very similar to those problems encountered in other domains where machine learning is applied. Of special interest is the challenges with large and often unbalanced datasets, interpretation of models and reliability in predictions.
The special session on 'Machine Learning for Drug Discovery' will cover anything related to QSAR and it will serve as an opportunity for QSAR practitioners to meet with scientists developing new theories in machine learning and with those who apply machine learning in other domains.