Health Informatics: A Computational Perspective in Healthcare: 932 - Brossura

Brossura

ISBN 10: 9811597375 ISBN 13: 9789811597374

Casa editrice: Springer, 2022

Riassunto

This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help ofcomputing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

 

 

Su questo libro

Informazioni sull?autore

Dr. Ripon Patgiri is currently working as an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar. He has received his B.Tech., M.Tech. and Ph.D. degree from the Institutions of Electronics and Telecommunication Engineers, Indian Institute of Technology Guwahati and National Institute of Technology Silchar, respectively. His research interests are big data, bioinformatics and distributed systems. He has published several papers in reputed journals, conferences and books. Also, he was General Chair of 6th International Conference on Advanced Computing, Networking and Informatics. Currently, he is General Chair of International Conference on Big Data, Machine Learning and Applications to be held during 16–19 December 2019 at National Institute of Technology Silchar. Moreover, he is an organizing chair of 25th International Symposium Frontiers of Research in Speech and Music (FRSM 2020), to be held during 08–09 October 2020. He is also an organizing chair of International Conference on Modeling, Simulations and Optimizations (CoMSO 2020), to be held during 3–5 August 2020. Furthermore, he is a Guest Editor of “Big Data: Exascale computation and beyond” in EAI Transaction on Scalable Information Systems and Guest Editor of “Internet of Things: Challenges and Solutions” in “EAI Transactions on Internet of Things“”. He reviewed many research articles from KSII Transactions on Internet and Information Systems, Electronics Letters, EAI Endorsed Transactions on Energy Web, EAI Endorsed Transactions on Scalable Information Systems, ACM Transactions on Knowledge and Data Engineering, IET Software, International Journal of Computational Vision and Robotics, Journal of Computer Science, International Journal of Advanced Computer Science and Applications and IEEE Access. Also, he served as TPC member in many conferences. He is a senior member of IEEE, member of ACM, EAI and ACCS and associate member of IETE.

Dr. Anupam Biswas is currently working as an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar. He has received his B.Tech., M.Tech. and Ph.D. degree from Dibrugarh University, Motilal Nehru National Institute of Technology Allahabad and Indian Institute of Technology (BHU) Varanasi respectively. His research interests are social networking, review mining, sentiment analysis, machine learning and soft computing. He has received the Best Paper Award for the paper titled “Community Detection in Multiple Featured Social Network using Swarm Intelligence” in International Conference on Communication and Computing (ICC-2014), Bangalore. Also, he has received Reviewer Award from Applied Soft Computing Journal (IF 3.541), Elsevier, 2015 and 2017, and Physica A: Statistical Mechanics and its Applications (IF 2.243), Elsevier, 2016. He has published several papers in reputed journals, conferences and books. He is a reviewer of IEEE Transactions on Fuzzy Systems (TFS), IEEE Transactions on Evolutionary Computation (IEEETEVC), IEEE Systems Journal (IEEE-SJ), IEEE Transactions on Systems, Man and Cybernatics: System (IEEE TSMC), Applied Soft Computing (ASOC), ACM Transactions on Knowledge Discovery from Data (TKDD), ACM Transactions on Intelligent Systems and Technology (TIST) and Physica A: Statistical Mechanics and its Applications and Information Sciences.

Dr. Pinki Roy is currently working as an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar. Dr. Pinki Roy received her B.Tech. degree in Computer Science & Engineering from Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra (2002, First class with distinction) and M.Tech. degree (2004, First class with distinction) from Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra. She has received her Ph.D. degree in the year 2014 in the field of Language Identification from National Institute of Technology, Silchar, Assam-788010, India. She was working as a Lecturer in Naval Institute of Technology, Colaba, Mumbai, India. (from February 2004 to August 2004). Her research interests include language identification, speech processing, machine intelligence and cloud computing. She has published several papers in reputed journals, conferences and books. She has received several awards which are listed below—1. “Distinguished Alumnus Award”, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, 2014. 2. “Young Scientist Award”, Venus International Foundation, Chennai, 2015. Awarded for major contribution in research during Ph.D. 3. “Rastriya Gaurav Award”, India International Friendship Society, New Delhi, 2015. 4. “Bharat Excellence Award”, Friendship Forum, New Delhi, 2016. 5. “Best Golden personalities Award”, Friendship Forum, New Delhi, 2016. 6. “Global Award for Education”, Friendship Forum, New Delhi, 2016. 7. Honoured as one of the “Most Distinguished Lady Alumni” by Computer Engineering Department of Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India.

 

Dalla quarta di copertina

This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help ofcomputing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

 

 

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 9811597375
• ISBN 13: 9789811597374
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 388
• Redattore: Patgiri Ripon, Biswas Anupam, Roy Pinki
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania