9786207997701 - current trends in orthodontic machine learning: advancements in ai-powered diagnostics, treatment planning, and predictive analytics in orthodontics di m., hemanth; shaji, sanjana; waremani, afshan saman (11 risultati)

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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Current Trends in Orthodontic Machine learning | Advancements in AI-Powered Diagnostics, Treatment Planning, and Predictive Analytics in Orthodontics | Hemanth M. (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786207997701 | Verantwortliche Person für die EU: SIA Om…niScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 104 pp. Englisch.

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Paperback. Condizione: new. Paperback. This book explores the transformative role of machine learning (ML) in modern orthodontics, emphasizing how AI-driven technologies enhance diagnosis, treatment planning, and clinical outcomes. It introduces the basics of ML and deep learning, highlighting their capabilities in analyzing vas…t dental datasets and learning patterns from clinical cases. The book reviews various ML models-such as artificial neural networks, convolutional neural networks, and genetic algorithms-and their accuracy in tasks like cephalometric landmark detection, growth prediction, extraction decisions, and treatment outcome forecasting. It discusses the development of clinical decision support systems (CDSS) powered by ML, enabling more consistent and objective treatment recommendations. Numerous studies are reviewed to showcase ML's application in areas like facial analysis, skeletal maturity assessment, orthognathic surgery planning, and remote care. Despite challenges like data standardization and model generalization, ML holds strong promise in improving diagnostic precision and personalizing orthodontic care. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book explores the transformative role of machine learning (ML) in modern orthodontics, emphasizing how AI-driven technologies enhance diagnosis, treatment planning, and clinical outcomes. It introduces the basics of ML and deep le…arning, highlighting their capabilities in analyzing vast dental datasets and learning patterns from clinical cases. The book reviews various ML models-such as artificial neural networks, convolutional neural networks, and genetic algorithms-and their accuracy in tasks like cephalometric landmark detection, growth prediction, extraction decisions, and treatment outcome forecasting. It discusses the development of clinical decision support systems (CDSS) powered by ML, enabling more consistent and objective treatment recommendations. Numerous studies are reviewed to showcase ML's application in areas like facial analysis, skeletal maturity assessment, orthognathic surgery planning, and remote care. Despite challenges like data standardization and model generalization, ML holds strong promise in improving diagnostic precision and personalizing orthodontic care.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book explores the transformative role of machine learning (ML) in modern orthodontics, emphasizing how AI-driven technologies enhance diagnosis, treatment planning, and clinical outcomes. It introduces the basics of ML and deep lea…rning, highlighting their capabilities in analyzing vast dental datasets and learning patterns from clinical cases. The book reviews various ML models-such as artificial neural networks, convolutional neural networks, and genetic algorithms-and their accuracy in tasks like cephalometric landmark detection, growth prediction, extraction decisions, and treatment outcome forecasting. It discusses the development of clinical decision support systems (CDSS) powered by ML, enabling more consistent and objective treatment recommendations. Numerous studies are reviewed to showcase ML's application in areas like facial analysis, skeletal maturity assessment, orthognathic surgery planning, and remote care. Despite challenges like data standardization and model generalization, ML holds strong promise in improving diagnostic precision and personalizing orthodontic care.

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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