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Springer Data Driven Approaches on Medical Imaging - Springer

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Description

Data Driven Approaches on Medical Imaging by Springer provides a comprehensive exploration of how machine learning and data science transform modern healthcare diagnostics and treatment planning. This technical resource covers the intersection of artificial intelligence and medical imaging, presenting methodologies for leveraging large datasets to improve image analysis, diagnostic accuracy, and clinical outcomes. Written for researchers, clinicians, and computer scientists, the book examines practical applications of data-driven techniques in radiology, pathology, and other imaging disciplines. The text combines theoretical foundations with real-world case studies, offering readers the knowledge to implement advanced computational methods in medical imaging workflows. Whether you are developing imaging algorithms, conducting healthcare research, or seeking to understand AI's role in diagnostics, this Springer publication delivers expert insights into this rapidly evolving field.

Key Features

Springer publication offering in-depth coverage of data-driven methodologies applied to medical imaging and diagnostic technology.

Combines machine learning fundamentals with practical applications in healthcare imaging, radiology, and clinical diagnostics.

Suitable for researchers, computer scientists, and healthcare professionals developing or implementing AI-based imaging solutions.

Covers theoretical frameworks and real-world case studies demonstrating data science techniques in modern medical practice.

Technical resource addressing the integration of artificial intelligence with imaging modalities for improved clinical outcomes.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
02 February 2024
Listed Since
30 September 2023

Barcode

No barcode data available

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