AI in Drug Discovery: First International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Lugano, Switzerland, September 19, 2024, Proceedings (Lecture Notes in Computer Science, 14894)

AI in Drug Discovery: First International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Lugano, Switzerland, September 19, 2024, Proceedings (Lecture Notes in Computer Science, 14894)
by: Djork-Arné Clevert (Editor),Michael Wand (Editor),Kristína Malinovská (Editor),Jürgen Schmidhuber (Editor),Igor V. Tetko (Editor)
Publisher: Springer
Edition: 2025th
Publication Date: 2024/9/27
Language: English
Print Length: 214 pages
ISBN-10: 3031723805
ISBN-13: 9783031723803
Book Description
This open Access book 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.The 12 papers presented here were carefully reviewed and selected for these open access proceedings. 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.
About the Author
This open Access book 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.The 12 papers presented here were carefully reviewed and selected for these open access proceedings. 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. Read more