AI in drug discovery

AI in drug discovery

المؤلف
Djork-Arné Clevert, Michael Wand, Kristína Malinovská, Jürgen Schmidhuber and Igor V. Tetko
سنة النشر
2025
الناشر
Springer
لغة الملف
انكليزي
نوع الملف
Book
تصنيف الكتاب
Computer Science

Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.


الكلمات المفتاحية: Big data / Deep learning / Drug discovery / Convolution neural networks toxicity / Synthesis planning / Chemo-informatics / GNNs / Ttransformers / Explainable AI / Active learning / Feature decomposition / Solvent effects / Molecular property prediction / Convergent routes / Structure-based drug discovery / Constraints