AI in Drug Discovery

First International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Lugano, Switzerland, September 19, 2024, Proceedings

Djork-Arné Clevert, Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko (Herausgeber)

Buch | Softcover

XXXVIII, 176 Seiten

2024 | 2025
Springer International Publishing (Verlag)
978-3-031-72380-3 (ISBN)

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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.

Erscheinungsdatum	27.09.2024
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	XXXVIII, 176 p. 50 illus., 49 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Naturwissenschaften ► Chemie ► Physikalische Chemie
Schlagworte	Active learning • Big Data • chemo-informatics • constraints • convergent routes • convolution neural networks toxicity • Deep learning • de novo molecular design • drug discovery • equivariant graph neural networks • Explainable AI • feature decomposition • GNNS • molecular property prediction • open access • quantum-mechanical properties • solvent effects • Structure-Based Drug Discovery • Synthesis Planning • Transformers
ISBN-10	3-031-72380-5 / 3031723805
ISBN-13	978-3-031-72380-3 / 9783031723803
Zustand	Neuware