This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniquesand deploying novel technologies in intelligent healthcare services and applications.
- Describes the advances of computing methodologies for life and medical science data;
- Presents applications of artificial intelligence in healthcare along with case studies and datasets;
- Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
Daftar Isi
Introduction.- Part –I Medical Expert Systems.- Mobile Agents in Healthcare.- Fuzzy Expert Systems in Medical Domain.- Expert Systems for Bioinformatics.- Virtual Reality and Augmented Realty support systems.- Brain Computer Interface for rehabilitation.- Robotics in healthcare.- Part –II Machine Learning in Healthcare.- Rule based Learning in Healthcare.- Classification and Regression in Healthcare.- Clustering algorithms.- Deep Learning in Healthcare.- Big Data.- Nature Inspired Algorithms.- Part III Case Studies.- Corona Virus Study.- Dementia Prediction.- Brain Injury Data Analysis.- Pesticide data Analysis for cancer detection.- Conclusion.
Tentang Penulis
Dr. Surbhi Bhatia received her doctorate from Banasthali Vidyapith, Rajasthan in 2018. She is currently teaching in King Faisal University, Saud Arabia in the department of Information systems, College of computer science and information technology. She has rich 8 years of teaching and academic experience in different universities including KR Mangalam University, Amity University, Manav Rachna International University. She received her BTech and Mtech in Computer science and Engineering from reputed Indian Universities. She is in the Editorial board member with Inderscience Publishers in the International Journal of Hybrid Intelligence, associated with IGI global and also with IEEE Conferences. She is currently editing two books and has published 6 patents in India.
Dr. Ashutosh Kumar Dubey is an expert in the field of Data Mining, Artificial Intelligence and Optimization. He is in the Computer Science and Engineering department in Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He is Senior Member of IEEE, Professional Member of ACM, Member of IACSIT and IAENG. He is also the Member of IEEE Computer Society Technical Committee on Computer Architecture, Computer Communications, Intelligent Informatics, Software Engineering, Computational Life Sciences, Cloud Computing Community and Smart Grid Community. He has more than 13 years of teaching experience. He has authored a book name Database Management Concepts. He is also heading the organization name ACCENT Social and Welfare Society from 2011. The main aim of this society is to encourage the activities of research and developments through organizing/sponsoring conferences and workshop. He has been associated with many international and national conferences as the Technical Program Committee member and Advisory Board Member. He is also associated as the Editorial Board Member/ Reviewer of many peer-reviewed journals including Elsevier, Springer, BMJ, IOS Press, Bentham Science, Thieme Publishing Group, etc. His research areas are Data Mining, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence, Big Data, Io T and Object-Oriented Programming.
Dr. Rita Chhikara has an excellent teaching experience of more than 20 years in various esteemed institutions. She is BTech from Pune University, received Mtech CSE degree from Punjab Technical University. MBA IT from Sikkim and Manipal University and has completed her Ph D from The North cap University (NCU) in Data Mining. She has completed a project titled ‘Neural Network based Steganalysis’ funded by the Department of Science and Technology (DST) and is currently working on project titled ‘Detecting Dementia using Deep Neural Network’ funded by DST, CSRI. Her current areas of research include Data Mining, Pattern Recognition, Machine Learning, Image Processing and Deep Learning. She has guided around 20 BTech projects, 12 Mtech thesis and currentlyguiding 5 Ph D Scholars. She has Published 35 Papers in peer reviewed International Journals with good indexing and reputed national/international conference proceedings. Her citation number since 2015 is 139. She has chaired a session at IEEE conference, ISMS Malaysia 2015 and received excellent paper award for research work presented at ICCI-SEM-2019, Singapore. She is recipient of ‘Teaching and Research Excellence National Award’. Optum Technologies had invited her to deliver a talk on emerging technology of Machine Learning in Ted Ed 2018. She is member of ISTE, ACM, IEEE and IET. She is reviewer for International Journal of Computer Science and Information Security (ESCI) and Editorial member of Journal Progress in Human Computer Interaction, Whioce Publishing, Singapore.
Ms. Poonam Chaudhary is currently working as an Assistant Professor in Department of CSE & IT, North Cap University, India. She has more than nine years of experience in teaching as an Assistant Professor and two years of industry experience as a Software Engineer at EIEL, New Delhi. She has completed her BTech from University of Rajasthan, Jaipur followed by Mtech from CITM, Faridabad affiliated by MDU Rohtak. Currently, she is pursuing Ph D from MRIIRS Faridabad in the field of Brain Computer Interfacing using EEG signals. . She has also completed GIAN course on “Brain Computer Interfaces” at IIT Guwahati and GIAN course on “Machine Learning” at MNIT Jaipur. She was mentor of four startup projects in the field of computer science. She has 10+ publications to her credit in various leading International and National Journals/Conferences in the various areas like Brain Computer Interfacing, Data Mining and Machine Learning. She has published one Indian patent also. Abhishek Kumar is Doctorate in computer science from University of Madras and done M.tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 7 years with more than 80 publications in reputed, peer reviewed National and International Journals, books & Conferences. His research area includes- Artificial intelligence, Image processing, Computer Vision, Data Mining, Machine Learning. He has been Session chair and keynote Speaker of many International conferences, webinars in India and Abroad. He has been the reviewer for IEEE and Inderscience Journal. He has authored/Co-Authored 6 books published internationally and edited 16 book etc. He has been member of various National and International professional societies in the field of engineering & research like Senior Member of
IEEE ,
IAENG (International Association of Engineers), Associate Member of
IRED (Institute of Research Engineers and Doctors), He has got Sir CV Raman National award for 2018 in young researcher and faculty Category from IJRP Group..He is Editorof Special issue in the
Journal Computer materials and continua
and Intelligent Automation and Soft Computing Cognitive Neurodynamics, Springer.