Synopsis
The integration of reinforcement learning techniques like Deep Q-Networks (DQNs)with computational intelligence is revolutionizing healthcare by enabling more accurate, timely, and personalized medical decision-making. These AI strategies enhance diagnostics, treatment planning, and patient monitoring by leveraging real-time data from sources such as IoT devices and medical imaging. This shift not only improves patient outcomes but also supports more efficient use of healthcare resources. As AI becomes more embedded in clinical practice, it plays a critical role in transforming healthcare into a more data-driven, adaptive, and patient-centered system. Applied AI and Computational Intelligence in Diagnostics and Decision-Making explores the fusion of reinforcement learning, particularly DQNs, with computational intelligence to enhance decision-making in healthcare. It delves into AI-driven diagnostics, personalized treatment plans, and real-time monitoring, leveraging deep learning and IoT integration. Covering topics such as artificial intelligence, neural networks, and remote patient monitoring, this book is an excellent resource for AI researchers, data scientists, machine learning engineers, computational intelligence specialists, medical professionals, radiologists, clinicians, and more.
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About the Author
Sachin Jain is an Assistant Professor in the Department of Computer Science and Engineering at Ajay Kumar Garg Engineering College, Ghaziabad. His research interests lie in Artificial Intelligence, Deep Learning and Machine Learning. He is a UGC-NET qualified teacher. He has published several research papers in Peer-Reviewed Journals and Conference proceedings. Mr. Jain has filed several patents for his work.
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Applied AI and Computational Intelligence in Diagnostics and Decision-Making
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Hardcover. Condition: new. Hardcover. The integration of reinforcement learning techniques like Deep Q-Networks (DQNs)with computational intelligence is revolutionizing healthcare by enabling more accurate, timely, and personalized medical decision-making. These AI strategies enhance diagnostics, treatment planning, and patient monitoring by leveraging real-time data from sources such as IoT devices and medical imaging. This shift not only improves patient outcomes but also supports more efficient use of healthcare resources. As AI becomes more embedded in clinical practice, it plays a critical role in transforming healthcare into a more data-driven, adaptive, and patient-centered system. Applied AI and Computational Intelligence in Diagnostics and Decision-Making explores the fusion of reinforcement learning, particularly DQNs, with computational intelligence to enhance decision-making in healthcare. It delves into AI-driven diagnostics, personalized treatment plans, and real-time monitoring, leveraging deep learning and IoT integration. Covering topics such as artificial intelligence, neural networks, and remote patient monitoring, this book is an excellent resource for AI researchers, data scientists, machine learning engineers, computational intelligence specialists, medical professionals, radiologists, clinicians, 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. Seller Inventory # 9798337333113
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Applied AI and Computational Intelligence in Diagnostics and Decision-Making (Hardcover)
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Hardcover. Condition: new. Hardcover. The integration of reinforcement learning techniques like Deep Q-Networks (DQNs)with computational intelligence is revolutionizing healthcare by enabling more accurate, timely, and personalized medical decision-making. These AI strategies enhance diagnostics, treatment planning, and patient monitoring by leveraging real-time data from sources such as IoT devices and medical imaging. This shift not only improves patient outcomes but also supports more efficient use of healthcare resources. As AI becomes more embedded in clinical practice, it plays a critical role in transforming healthcare into a more data-driven, adaptive, and patient-centered system. Applied AI and Computational Intelligence in Diagnostics and Decision-Making explores the fusion of reinforcement learning, particularly DQNs, with computational intelligence to enhance decision-making in healthcare. It delves into AI-driven diagnostics, personalized treatment plans, and real-time monitoring, leveraging deep learning and IoT integration. Covering topics such as artificial intelligence, neural networks, and remote patient monitoring, this book is an excellent resource for AI researchers, data scientists, machine learning engineers, computational intelligence specialists, medical professionals, radiologists, clinicians, 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. Seller Inventory # 9798337333113
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Applied AI and Computational Intelligence in Diagnostics and Decision-Making (Hardcover)
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Hardcover. Condition: new. Hardcover. The integration of reinforcement learning techniques like Deep Q-Networks (DQNs)with computational intelligence is revolutionizing healthcare by enabling more accurate, timely, and personalized medical decision-making. These AI strategies enhance diagnostics, treatment planning, and patient monitoring by leveraging real-time data from sources such as IoT devices and medical imaging. This shift not only improves patient outcomes but also supports more efficient use of healthcare resources. As AI becomes more embedded in clinical practice, it plays a critical role in transforming healthcare into a more data-driven, adaptive, and patient-centered system. Applied AI and Computational Intelligence in Diagnostics and Decision-Making explores the fusion of reinforcement learning, particularly DQNs, with computational intelligence to enhance decision-making in healthcare. It delves into AI-driven diagnostics, personalized treatment plans, and real-time monitoring, leveraging deep learning and IoT integration. Covering topics such as artificial intelligence, neural networks, and remote patient monitoring, this book is an excellent resource for AI researchers, data scientists, machine learning engineers, computational intelligence specialists, medical professionals, radiologists, clinicians, 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. Seller Inventory # 9798337333113
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