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portada Swarm Optimization for Biomedical Applications
Type
Physical Book
Publisher
Author
Language
English
Pages
302
Format
Hardcover
ISBN13
9781032697338
Edition No.
1

Swarm Optimization for Biomedical Applications

Mallik Saurav,Zhao Zhongming,Jana Nanda Dulal (Author) · Crc Press · Hardcover

Swarm Optimization for Biomedical Applications - Mallik Saurav,Zhao Zhongming,Jana Nanda Dulal

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Synopsis "Swarm Optimization for Biomedical Applications"

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 medical 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.

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