Sinopsis
Artificial intelligence (AI) is evolving rapidly, moving from predictive systems toward a new era dominated by generative technologies. Among the most influential advances are language models, which have expanded into diverse forms capable of addressing increasingly complex and domain-specific challenges. One of the most transformative developments is the emergence of vision language models (VLMs), which integrate visual and textual understanding to enable richer forms of analysis and interaction. By learning relationships between images and text through large-scale training, these models open new possibilities for applications that require deeper contextual interpretation of visual data. In healthcare, VLMs are particularly promising, supporting innovations such as visual question answering, automated medical report interpretation, and enhanced diagnostic and analytical capabilities. Vision Language Models for Next-Generation Healthcare provides one of the first comprehensive explorations of VLMs in healthcare, highlighting how their multimodal capabilities can transform diagnostics, clinical decision-making, and patient care. By combining insights from computer science, biomedical engineering, and clinical practice, this book offers a unified reference on VLMs tailored for healthcare. Covering topics such as augmented report generation, radiology, and workflow intelligence, this book is a critical emerging resource for graduate and doctoral students, computer scientists, biomedical engineers, healthcare informatics, medical researchers, and more.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Pethuru Raj, PhD is a chief architect at Reliance Jio Platforms Ltd. (JPL) Bangalore. I previously worked in IBM Global Cloud Centre of Excellence (CoE), Wipro consulting services (WCS), and Robert Bosch Corporate Research (CR). I have gained over 22 years of IT industry experience and eight years of research experience. Finished the CSIR-sponsored PhD degree at Anna University, Chennai, and continued with the UGC-sponsored postdoctoral research in the Department of Computer Science and Automation, Indian Institute of Science (IISc), Bangalore. After that, I was granted two international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. I am an IEEE and ACM Professional member. I am focusing on some of the emerging technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI) Model Optimization Techniques, Prompt Engineering, large Language Models (LLMs), Efficient, Explainable, and Edge AI, Blockchain, Digital Twins, Cloud-native and edge computing, Green and Generative AI, High-Performance Computing (HPC) and Quantum Computing, Platform Engineering, 5G/6G, etc.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Hardcover. Condición: new. Hardcover. Artificial intelligence (AI) is evolving rapidly, moving from predictive systems toward a new era dominated by generative technologies. Among the most influential advances are language models, which have expanded into diverse forms capable of addressing increasingly complex and domain-specific challenges. One of the most transformative developments is the emergence of vision language models (VLMs), which integrate visual and textual understanding to enable richer forms of analysis and interaction. By learning relationships between images and text through large-scale training, these models open new possibilities for applications that require deeper contextual interpretation of visual data. In healthcare, VLMs are particularly promising, supporting innovations such as visual question answering, automated medical report interpretation, and enhanced diagnostic and analytical capabilities. Vision Language Models for Next-Generation Healthcare provides one of the first comprehensive explorations of VLMs in healthcare, highlighting how their multimodal capabilities can transform diagnostics, clinical decision-making, and patient care. By combining insights from computer science, biomedical engineering, and clinical practice, this book offers a unified reference on VLMs tailored for healthcare. Covering topics such as augmented report generation, radiology, and workflow intelligence, this book is a critical emerging resource for graduate and doctoral students, computer scientists, biomedical engineers, healthcare informatics, medical researchers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798337373157
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Hardcover. Condición: new. Hardcover. Artificial intelligence (AI) is evolving rapidly, moving from predictive systems toward a new era dominated by generative technologies. Among the most influential advances are language models, which have expanded into diverse forms capable of addressing increasingly complex and domain-specific challenges. One of the most transformative developments is the emergence of vision language models (VLMs), which integrate visual and textual understanding to enable richer forms of analysis and interaction. By learning relationships between images and text through large-scale training, these models open new possibilities for applications that require deeper contextual interpretation of visual data. In healthcare, VLMs are particularly promising, supporting innovations such as visual question answering, automated medical report interpretation, and enhanced diagnostic and analytical capabilities. Vision Language Models for Next-Generation Healthcare provides one of the first comprehensive explorations of VLMs in healthcare, highlighting how their multimodal capabilities can transform diagnostics, clinical decision-making, and patient care. By combining insights from computer science, biomedical engineering, and clinical practice, this book offers a unified reference on VLMs tailored for healthcare. Covering topics such as augmented report generation, radiology, and workflow intelligence, this book is a critical emerging resource for graduate and doctoral students, computer scientists, biomedical engineers, healthcare informatics, medical researchers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798337373157
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Hardcover. Condición: new. Hardcover. Artificial intelligence (AI) is evolving rapidly, moving from predictive systems toward a new era dominated by generative technologies. Among the most influential advances are language models, which have expanded into diverse forms capable of addressing increasingly complex and domain-specific challenges. One of the most transformative developments is the emergence of vision language models (VLMs), which integrate visual and textual understanding to enable richer forms of analysis and interaction. By learning relationships between images and text through large-scale training, these models open new possibilities for applications that require deeper contextual interpretation of visual data. In healthcare, VLMs are particularly promising, supporting innovations such as visual question answering, automated medical report interpretation, and enhanced diagnostic and analytical capabilities. Vision Language Models for Next-Generation Healthcare provides one of the first comprehensive explorations of VLMs in healthcare, highlighting how their multimodal capabilities can transform diagnostics, clinical decision-making, and patient care. By combining insights from computer science, biomedical engineering, and clinical practice, this book offers a unified reference on VLMs tailored for healthcare. Covering topics such as augmented report generation, radiology, and workflow intelligence, this book is a critical emerging resource for graduate and doctoral students, computer scientists, biomedical engineers, healthcare informatics, medical researchers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798337373157
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Buch. Condición: Neu. Vision Language Models for Next-Generation Healthcare | Pethuru Raj (u. a.) | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337373157 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 135298987
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence (AI) is evolving rapidly, moving from predictive systems toward a new era dominated by generative technologies. Among the most influential advances are language models, which have expanded into diverse forms capable of addressing increasingly complex and domain-specific challenges. One of the most transformative developments is the emergence of vision language models (VLMs), which integrate visual and textual understanding to enable richer forms of analysis and interaction. By learning relationships between images and text through large-scale training, these models open new possibilities for applications that require deeper contextual interpretation of visual data. In healthcare, VLMs are particularly promising, supporting innovations such as visual question answering, automated medical report interpretation, and enhanced diagnostic and analytical capabilities. Vision Language Models for Next-Generation Healthcare provides one of the first comprehensive explorations of VLMs in healthcare, highlighting how their multimodal capabilities can transform diagnostics, clinical decision-making, and patient care. By combining insights from computer science, biomedical engineering, and clinical practice, this book offers a unified reference on VLMs tailored for healthcare. Covering topics such as augmented report generation, radiology, and workflow intelligence, this book is a critical emerging resource for graduate and doctoral students, computer scientists, biomedical engineers, healthcare informatics, medical researchers, and more. Nº de ref. del artículo: 9798337373157
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