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Publicado por LAP LAMBERT Academic Publishing Jan 2025, 2025
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -AI and machine learning (ML) are increasingly transforming the field of radiopharmaceutical development, offering new ways to design, optimize, and evaluate these critical compounds. Radiopharmaceuticals, which are used for both diagnostic imaging and targeted therapy, require precise formulation and testing to ensure safety and efficacy. AI and ML technologies can accelerate this process by analyzing vast amounts of complex data, identifying patterns, and making predictions that were previously time-consuming or difficult.Machine learning algorithms, such as deep learning and reinforcement learning, are used to model molecular interactions, predict the behavior of radiopharmaceuticals within the body, and optimize the selection of radioisotopes for specific targeting. AI-driven tools also enable faster drug discovery by simulating and predicting the outcomes of radiopharmaceutical interactions with biological systems, thus reducing the need for extensive trial and error.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208418275 ISBN 13: 9786208418274
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Añadir al carritoTaschenbuch. Condición: Neu. AI and Machine Learning in Radiopharmaceutical Development | "From Design to Therapy: The Impact of AI in Radiopharmaceutical Development" | Khushboo Gupta (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208418274 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por LAP LAMBERT Academic Publishing Jan 2025, 2025
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2025
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Publicado por LAP LAMBERT Academic Publishing, 2025
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Publicado por LAP Lambert Academic Publishing, 2025
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Añadir al carritoPaperback. Condición: new. Paperback. AI and machine learning (ML) are increasingly transforming the field of radiopharmaceutical development, offering new ways to design, optimize, and evaluate these critical compounds. Radiopharmaceuticals, which are used for both diagnostic imaging and targeted therapy, require precise formulation and testing to ensure safety and efficacy. AI and ML technologies can accelerate this process by analyzing vast amounts of complex data, identifying patterns, and making predictions that were previously time-consuming or difficult.Machine learning algorithms, such as deep learning and reinforcement learning, are used to model molecular interactions, predict the behavior of radiopharmaceuticals within the body, and optimize the selection of radioisotopes for specific targeting. AI-driven tools also enable faster drug discovery by simulating and predicting the outcomes of radiopharmaceutical interactions with biological systems, thus reducing the need for extensive trial and error. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Publicado por LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208418275 ISBN 13: 9786208418274
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - AI and machine learning (ML) are increasingly transforming the field of radiopharmaceutical development, offering new ways to design, optimize, and evaluate these critical compounds. Radiopharmaceuticals, which are used for both diagnostic imaging and targeted therapy, require precise formulation and testing to ensure safety and efficacy. AI and ML technologies can accelerate this process by analyzing vast amounts of complex data, identifying patterns, and making predictions that were previously time-consuming or difficult.Machine learning algorithms, such as deep learning and reinforcement learning, are used to model molecular interactions, predict the behavior of radiopharmaceuticals within the body, and optimize the selection of radioisotopes for specific targeting. AI-driven tools also enable faster drug discovery by simulating and predicting the outcomes of radiopharmaceutical interactions with biological systems, thus reducing the need for extensive trial and error.