4 papers
Temporal Distribution Shift in Real-World Pharmaceutical Data: Implications for Uncertainty Quantification in QSAR Models
Hannah Rosa Friesacher, Emma Svensson, Susanne Winiwarter +3
The estimation of uncertainties associated with predictions from quantitative structure-activity relationship (QSAR) models can accelerate the drug discovery process by identifying…
Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models
Hannah Rosa Friesacher, Ola Engkvist, Lewis Mervin +2
In the drug discovery process, where experiments can be costly and time-consuming, computational models that predict drug-target interactions are valuable tools to accelerate the d…
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
Martijn Oldenhof, Edward De Brouwer, Adam Arany +1
Identifying the chemical structure from a graphical representation, or image, of a molecule is a challenging pattern recognition task that would greatly benefit drug development. Y…
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
Martijn Oldenhof, Adam Arany, Yves Moreau +1
Training object detection models usually requires instance-level annotations, such as the positions and labels of all objects present in each image. Such supervision is unfortunate…