Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development, 1st edition

Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Health...

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Đã lưu trong:
Chi tiết về thư mục
Những tác giả chính: Kumar, Sandeep, Nayyar, Anand, Paul, Anand
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: Chapman and Hall/CRC 2020
Những chủ đề:
Truy cập trực tuyến:https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/93528
https://doi.org/10.1201/9780429289675
Các nhãn: Thêm thẻ
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Thư viện lưu trữ: Thư viện Trường Đại học Đà Lạt
Miêu tả
Tóm tắt:Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient’s life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world. Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world.