
SCEJ 91st Annual Meeting
Mar. 17 (Tue) - 19 (Thu), 2026
Yoshida Campus, Kyoto University
Japanese page
Most recent update: 2025-12-11 08:29:01
The keywords that frequently used in this topics code. | Keywords | Number | |
|---|---|---|---|
| Machine learning | 4 | ||
| Drug-drug interaction | 1 | ||
| ACKN No. | Title/Author(s) | Keywords | Style |
|---|---|---|---|
| 8 | Proposal of Crystal Structures for Novel Solid Electrolytes with High Ionic Conductivity Using Machine Learning | Solid Electrolyte Machine Learning Materials Informatics | P |
| 10 | Investigation of Highly-Accurate Variational Autoencoders for Multicomponent Crystal Structures | Machine Learning Crystal Structure VAE Latent Representation of Materials | P |
| 23 | Improving the predictive accuracy of drug-drug interaction prediction models using unlabeled, ingredient, and clinical data | Drug-drug interaction Machine learning Positive-unlabeled learning | P |
| 52 | Suggesting new drug candidates for schizophrenia using machine learning models and generative adversarial network | Machine learning Drug design Schizophrenia | P |
Organizing Committee of SCEJ 91st Annual Meeting (2026)
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