Connected healthcare systems are becoming increasingly popular due to their ability to collect and share patient data between healthcare providers, allowing for more comprehensive and coordinated care. However, the large amount of data collected can be overwhelming, and traditional methods of data analysis may not be sufficient to fully utilize this data. Soft Computing techniques, which include Artificial Neural Networks (ANNs), Fuzzy Logic, Genetic Algorithms (GAs), Machine Learning (ML), and Natural Language Processing (NLP), can provide solutions to the challenges faced in connected healthcare systems.

Soft Computing techniques are a subset of Artificial Intelligence (AI) that deal with uncertainty, imprecision, and incomplete information. They are designed to mimic human thinking and reasoning, and can handle complex and non-linear problems. These techniques have been applied in various fields, including finance, engineering, and manufacturing, and have shown promising results in healthcare. This book explores the application of Soft Computing techniques in connected healthcare systems, with a focus on enhancing services and improving patient outcomes. The book is divided into chapters, with each chapter covering a different Soft Computing technique and its applications in healthcare. The chapters provide practical examples and case studies to demonstrate the effectiveness of each technique, as well as discussing the benefits and limitations.

The book concludes with a discussion of the future of Soft Computing techniques in connected healthcare systems. We believe that Soft Computing techniques have the potential to revolutionize healthcare by providing more personalized and accurate services to patients, improving the accuracy of diagnoses, and optimizing treatment plans. We hope that this book will inspire further research and innovation in the field of connected healthcare systems, and provide a valuable resource for healthcare professionals, researchers, and students.

Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has published scientific research publications in reputed International Journals and Conferences, including SCI indexed and Scopus indexed Journals such as Cognitive Systems Research (Elsevier), Physical Communication(Elsevier), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis Group), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience) & Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has authored/co-authored chapters with International publishers like Elsevier, Springer, Wiley, and De Gruyter. He has authored/ edited four books with a National/International level publisher (CRC Press, Bhavya publications). His research area includes Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like IEEE, ISTE, IAENG, ICSES, UACEE, Internet Society, Universal Inovators research lab life membership, etc. He possesses teaching experience of more than 10 years. He is the co-convener of ICICC, DOSCI, ICDAM & ICCCN springer Scopus Indexed conference series and ICCRDA-2020 Scopus Indexed IOP Material Science & Engineering conference series. He is also the organizer and Co-Convener of the International Conference on Innovations and Ideas towards Patents (ICIIP) series. He is also the Advisory and TPC committee member of the ICCIDS-2022 Elsevier SSRN Conference. He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences. He also served as a session chair in many international springer conferences. He is currently a doctoral researcher at DCR University of Science & Technology, Haryana. He completed his Post Graduation in 2012 from SRM UNIVERSITY, NCR CAMPUS, GHAZIABAD, and Graduated in 2010 from KNGD MODI ENGG. COLLEGE, GBTU.

Prof. Suman Deswal holds a Ph.D. from DCR University of Science & Technology, Murthal, India. She completed her M.Tech (CSE) from Kurukshetra University, Kurukshetra, India, and B.Tech (Computer Science & Engg.) from CR State College of Engg., Murthal, India, in 2009 and 1998, respectively. She possesses 21 years of teaching experience and is presently working as a Professor in the Department of Computer Science and Engineering at DCR University of Science and Technology, Murthal, India. Her research area includes wireless networks, heterogeneous networks, distributed systems, Machine Learning, deep learning approaches and Bioinformatics. She has many research papers to her credit in reputed journals, including SCI, indexed, and Scopus indexed Journals and conferences. Her publications have more than 143 citations. She is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, and International IEEE & Springer Conferences. She is a member of IAENG and Computer Society of India (CSI).

Dr. Umesh Gupta is currently an Assistant Professor at the School of Computer Science Engineering and Technology at Bennett University, Times of India Group, Greater Noida, Uttar Pradesh, India. He received a Doctor of Philosophy (Ph.D.) (Machine Learning) from the National Institute of Technology, Arunachal Pradesh, India. He has awarded a gold medalist for his Master of Engineering (M.E.) from the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India, and Bachelor of Technology (B.Tech.) from Dr. APJ, Abdul Kalam Technical University, Lucknow, India. His research interests include SVM, ELM, RVFL, machine learning, and deep learning approaches. He has published over 35 referred journal and conference papers of international repute. His scientific research has been published in reputable international journals and conferences, including SCI-indexed and Scopus-indexed journals like Applied soft computing (Elsevier) and Applied Intelligence (Springer), each of which is a peer-reviewed journal. His publications have more than 158 citations with an h-index of 8 and an i10-index of 8 on Google Scholar as of March 1, 2023. He is a senior Member of IEEE (SMIEEE) and an active member of ACM, CSTA, and other scientific societies. He also reviewed papers for many scientific journals and conferences in the US and abroad. He led sessions at the 6th International conference (ICICC-2023), 3rd International Conference on Data Analytics and Management (ICDAM 2023), the 3rd International Conference on Computing and Communication Networks (ICCCN 2022), and other international conferences like Springer ETTIS 2022 and 2023. He is currently supervising two Ph.D. students. He is the co-principal investigator (co-PI) of TWO major research projects. He published three patents in the years 2021-2023. He also published four book chapters with Springer, CRC

MUJAHID TABASSUM is a lecturer at Noroff University College (Noroff Accelerate), Kristiansand, Norway. He has completed a Master of Science (Specialization in Computer System Engineering) degree from Halmstad University, Sweden, and a bachelor's degree from the University of Wollongong, Australia. He has worked in various International Universities in Malaysia and the Middle East, making his profile well reputed. He has managed and led several student and research projects and published several research articles in well-known SCI journals and Scopus conferences. He is a qualified "Chartered Engineer - CEng" registered with the Engineering Council, UK. He has 13 years of teaching experience. He is a Cisco, Microsoft, Linux, Security, and IoT certified instructor. His research interests include Computer Networks, AI, Wireless Sensor networks, IoT, Security, and Applications. He has published several Scopus papers, journals, and book chapters. He is a Member of IEEE, a Member of the Institution of Engineering and Technology, a Member of IAENG, a Member of the Australia Computing Society (ACS), and a Member of MBOT Malaysia. He is an active Society of IT Engineers and Researchers, UK.

Dr. Isah A. Lawal was an Erasmus Mundus Joint Doctorate Fellow with over ten years of professional work experience, including teaching and research. He has participated in several collaborative multidisciplinary research projects at different universities, including in Europe (Italy and United Kingdom) and the Middle East (Saudi Arabia). He has authored several articles in peer-reviewed journals and conferences ranging from data-driven predictive modeling to machine learning for intelligent systems. In addition to actively engaging in research, he has taught data mining, innovative systems, and artificial intelligent courses at both undergraduate and postgraduate levels. Dr. Isah's research interests include the multidisciplinary application of machine learning techniques, data mining, and smart systems. He has supervised and examined several undergraduate projects and master's thesis in Statistical Data Analysis, Data Visualisation, and Natural Language Processing. Dr. Isah is currently participating in the EEA granted data-driven public administration project as a consultant for the Department for Strategic Development and Coordination of Public Administration, Ministry of the Interior of the Czech Republic. The project involves using big data analytics to analyze public mobility from mobile positioning data, to efficiently plan and distribute public services and public administration in the Czech Republic.