Practical considerations for active machine learning in drug discovery
Active machine learning enables the automated selection of the most valuable next experiments to improve predictive modelling and hasten active retrieval in drug discovery. Although a long established theoretical concept and introduced to drug discovery approximately 15 years ago, the deployment of...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Elsevier BV
2020
|
| Online Access: | https://hdl.handle.net/1721.1/126410 |