Swarm Optimization Biomedical Applications (29 results)
- Softcover
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Paperback. Condition: Brand New. 302 pages. 6.14x0.74x9.21 inches. In Stock.
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Condition: New. Dr Saurav Mallik is a Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, USA. Prior to this, he was a Postdoctoral Fellow in the Department of Environmental Health, Harvard T H Chan School of Public Hea.
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- Hardcover
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Taschenbuch. Condition: Neu. Neuware - Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medi…cal diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.
Swarm Optimization for Biomedical Applications
Mallik, Saurav (EDT); Zhao, Zhongming (EDT); Jana, Nanda Dulal (EDT); Jayagopal, Prabhu (EDT); Si, Tapas (EDT)
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Swarm Optimization for Biomedical Applications
Mallik, Saurav (EDT); Zhao, Zhongming (EDT); Jana, Nanda Dulal (EDT); Jayagopal, Prabhu (EDT); Si, Tapas (EDT)
- Hardcover
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- Hardcover
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Swarm Optimization for Biomedical Applications
Mallik, Saurav (EDT); Zhao, Zhongming (EDT); Jana, Nanda Dulal (EDT); Jayagopal, Prabhu (EDT); Si, Tapas (EDT)
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Swarm Optimization for Biomedical Applications
Mallik, Saurav (EDT); Zhao, Zhongming (EDT); Jana, Nanda Dulal (EDT); Jayagopal, Prabhu (EDT); Si, Tapas (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
- International Edition
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Condition: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested… if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 326 pages. 9.18x6.12x9.21 inches. In Stock.
Language: English
Published by Taylor & Francis Np Exclusive(Cbs),, 2025
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Add to basketN.A. Condition: New. ISBN:9781032697338.
- Softcover
- Print on Demand
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Paperback. Condition: new. Paperback. Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medic…al diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering. With the recent advancements in machine learning (ML) and deep learning (DL), ML/DL techniques are being widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. Various optimization techniques have been employed to optimize parameters, hyper-parameters. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
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Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Softcover
- Print on Demand
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Paperback. Condition: new. Paperback. Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medic…al diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering. With the recent advancements in machine learning (ML) and deep learning (DL), ML/DL techniques are being widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. Various optimization techniques have been employed to optimize parameters, hyper-parameters. 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.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Paperback. Condition: new. Paperback. Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medic…al diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering. With the recent advancements in machine learning (ML) and deep learning (DL), ML/DL techniques are being widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. Various optimization techniques have been employed to optimize parameters, hyper-parameters. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
