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Record Nr. |
UNINA9910890900403321 |
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Titolo |
AI in Drug Discovery : First International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Lugano, Switzerland, September 19, 2024, Proceedings / / edited by Djork-Arné Clevert, Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XXXVIII, 176 p. 50 illus., 49 illus. in color.) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 14894 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Data mining |
Chemistry - Data processing |
Artificial Intelligence |
Data Mining and Knowledge Discovery |
Computational Chemistry |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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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. |
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