Intelligent decision support systems : applications in signal processing / edited by Surekha Borra, Nilanjan Dey, Siddhartha Bhattacharyya, Mohamed Salim Bouhlel

Description based on print version record

Includes bibliographical references and index

Frontmatter -- Preface -- Contents -- List of Contributors -- 1. Feature selection in biomedical signal classification process and current software implementations / Jovic, Alan -- 2. An overview of skin lesion segmentation, features engineering, and classification / Sabri, My Abdelouahed / Filali, Youssef / Ennouni, Assia / Yahyaouy, Ali / Aarab, Abdellah -- 3. Brain tumor image segmentation and classification using SVM, CLAHE, and ARKFCM / Ishita, Banerjee / Madhumathy, P. / Kavitha, N. -- 4. Coronary Heart Disease prediction using genetic algorithm based decision tree / Sivaranjani, Reddi / Naresh, Vankamamidi S. / Murthy, Nistala V.E.S. -- 5. Intelligent approach for retinal disease identification / Rajyaguru, Vipul C. / Vithalani, Chandresh H. / Thanki, Rohit M. -- 6. Speech separation for interactive voice systems / Wiem, Belhedi / Anouar, Ben Messaoud Mohamed / Aïcha, Bouzid -- 7. Machine vision for human-machine interaction using hand gesture recognition / Verma, Varnita / Rajput, Anshuman / Chauhan, Piyush / Rathore, Harshit / Goyal, Piyush / Gupta, Mukul Kumar -- Index

Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD)

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