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E-grāmata: Swarm Intelligence and Machine Learning: Applications in Healthcare

Edited by (Fac of Inf Tech, Vietnam), Edited by (Uni Ins of Tech, India), Edited by , Edited by (IPS Col of Tech & Manage, India), Edited by (Raj Gandhi Proudyo Vishwavid, India)
  • Formāts: 228 pages
  • Izdošanas datums: 29-Sep-2022
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9781000737615
  • Formāts - PDF+DRM
  • Cena: 62,60 €*
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  • Bibliotēkām
  • Formāts: 228 pages
  • Izdošanas datums: 29-Sep-2022
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9781000737615

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Today the healthcare sector is facing challenges such as detecting the cause of ailments, disease prevention, high operating costs, availability of skilled technicians and infrastructure bottlenecks. Intelligent healthcare management technologies are needed to manage these challenges. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data being generated for saving lives, reducing medical errors, enhancing efficiency, reducing costs and making the whole world a healthy place.

The book introduces techniques that developed using machine learning along with swarm intelligence in healthcare informatics. It also discusses one of the major applications of artificial intelligence: using machine learning to extract useful information from multimodal data optimally by using swarm intelligence. It reviews optimization methods that help to minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The objective of this book is to use swarm intelligence and machine learning techniques for various medical issues such as diagnosing cancer, brain tumor, diabetic retinopathy, heart diseases as well as drug design and development. The book will act as one-stop reference to think and explore swarm intelligence and machine learning algorithms seriously for real-time patient diagnosis.
1. An Intelligent Methodology for COVID-19 RISK Prediction using Swarm
Intelligence OptimizationA Machine Learning Perspective
2. Impact of COVID
Vaccination on the Globe using Data Analytics
3. Swarm Intelligence and
Machine Learning Algorithms for Cancer Diagnosis
4. Applications of Swarm
Intelligence and Machine Learning for COVID-19
5. Machine Learning for Rural
Healthcare
6. Swarm Intelligence-based Framework for Image Segmentation of
Knee MRI Images for Detection of Bone Cancer
7. Swarm Optimization and
Machine Learning to Improve the Detection of Brain Tumor
8. Analysis of
Machine Learning Algorithms for Prediction of Diabetes
9. Swarm Intelligence
for Diagnosis of Arrhythmia and Cardiac Stenosis
10. Design and Development
of Covid-19 Pandemic Situation-based Contactless Automated Teller Machine
Operations
11. Scope of Optimization in Plant Leaf Disease Detection using
Deep Learning and Swarm Intelligence
12. Automatic Speech Analysis of
Conversations for Dementia Detection Using Bi-LSTM Model
Shikha Agarwal, Dac-Nhuong Le