Mayuko Ogawa, Genko Oyama, et al.
Parkinsonism and Related Disorders
Computer-aided synthesis design, automation, and analytics assisted by machine learning are promising resources in the researcher’s toolkit. Each component may alleviate the chemist from routine tasks, provide valuable insights from data, and enable more informed experimental design. Herein, we highlight selected works in the field and discuss the different approaches and the problems to which they may apply. We emphasize that there are currently few tools with a low barrier of entry for non-experts, which may limit widespread integration into the researcher’s workflow.
Mayuko Ogawa, Genko Oyama, et al.
Parkinsonism and Related Disorders
Hiroki Yanagisawa
ICML 2023
Dimitrios Christofidellis, Giorgio Giannone, et al.
MRS Spring Meeting 2023
Brian Quanz, Pavithra Harsha, et al.
INFORMS 2022