Advanced Prognostic Predictive Modelling in Healthcare Data Analytics

1. Front Matter

   Pages i-xiv

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2. Data Visualization in the Transformation of Healthcare Industries

   • Gopi Battineni, Mamta Mittal, Shivani Jain

   Pages 1-23

3. Emerging Healthcare Problems in High-Dimensional Data and Dimension Reduction

   • Sudhansu Shekhar Patra, G. M. Harshvardhan, Mahendra Kumar Gourisaria, Jnyana Ranjan Mohanty, Subham Choudhury

   Pages 25-49

4. Applications of Fuzzy Logic in Bioinformatics: A Survey

   • Nabanita Konwar, Pradip Debnath

   Pages 51-69

5. Disease Prediction Using Data Mining and Machine Learning Techniques

   • Suvarna G. Kanakaraddi, Karuna C. Gull, Jyoti Bali, Ashok K. Chikaraddi, Shantala Giraddi

   Pages 71-92

6. Spatial Contextual Thresholding Technique: A Case Study to Detect Nodule of Thyroid in Ultrasound Images

   • Anshu Singla, Chetna Kaushal, Vatsala Anand

   Pages 93-106

7. Cognitive Intelligent Healthcare (CIH) Framework by Integration of IoT with Machine Learning for Classification of Electroencephalography (EEG)

   • V. Vedanarayanan, G. Arulselvi, D. Poornima

   Pages 107-127

8. Prognostic Modeling with the Internet of Healthcare Things Applications

   • Simran Kaur, Yasha Hasija

   Pages 129-155

9. Cancer Tissue Segmentation in Various Conditions with Semiautomatic and Automatic Approach

   • Ujwala Gaikwad, Kamal Shah

   Pages 157-177

10. Diabetes Prediction Using Machine Learning Approaches

    • Shawni Dutta, Samir Kumar Bandyopadhyay

    Pages 179-202

11. Prediction of Pneumonia from Chest X-Ray Images Using Pre-trained Convolutional Neural Networks

    • Venkata Krishna Kishore Kolli, Venkatramaphanikumar Sistla, Sasikala Vallabhajosyula

    Pages 203-215

12. Early Screening of COVID-19 from Chest CT Using Deep Learning Technique

    • Asmita Ray, Avantika Tiwari, D. Chandra Mouli

    Pages 217-239

13. A Probe into Performance Analysis of Real-Time Forecasting of Endemic Infectious Diseases Using Machine Learning and Deep Learning Algorithms

    • Manish Kumar Pandey, Prashant K. Srivastava

    Pages 241-265

14. Clinical Decision-Making and Predicting Patient Trajectories

    • Anup P. Bhat, Nitin G. Dumore, Sanjay J. Dhoble, Kishor G. Rewatkar

    Pages 267-311

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence.  The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.

• Prognostic Modelling
• Healthcare
• Image and Data Analysis
• Deep Neural Network
• Supervised Learning
• Classification
• Segmentation
• Predictive Modelling

“The book offers a collection of literature review, and discussions of the methods in computer sciences, artificial intelligence, machine learning and may offer materials for graduate students in biomedical engineering and healthcare communications. I certainly will recommend this book for individuals in data and predictive modelling especially when they are quantitatively inclined as the prognostic modelling techniques rely on mathematical and or statistical formulations.” (Reuben Adatorwovor, ISCB News, iscb.info, June, 2022)

• Department of Radiology, Washington University in St. Louis, St. Louis, USA

  Sudipta Roy

• Department of Computer Engineering, J. C. Bose University of Science and Technology, YMCA, Faridabad, India

  Lalit Mohan Goyal

• Department of Computer Science and Engineering, G. B. Pant Government Engineering College, New Delhi, India

  Mamta Mittal

Dr. Sudipta Roy has received his Ph.D. in Computer Science & Engineering from the Department of Computer Science and Engineering, University of Calcutta. He is an author of more than forty publications in refereed national/international journals and conferences including IEEE, Springer, Elsevier and many others. He is an author of one book and many book chapters. He holds an US patent in medical image processing and filed an Indian patent in smart agricultural system. He has served as a reviewer of many international journals including IEEE, Springer, Elsevier, IET and many others, and international conferences. He has served as an international advisory committee member and a program committee member of AICAE-2019, INDIACom-2019, CAAI 2018, ICAITA-2018, ICSESS-2018, INDIACom-2018, ISICO-2017, AICE-2017 and many more conferences. He is serving as Associate Editor of IEEE Access, IEEE and International Journal of Computer Vision and Image Processing (IJCVIP), IGI Global Journal. He has more than five years of experience in teaching and research. His fields of research interests are healthcare image analysis, image processing, steganography, artificial intelligence, big data analysis, machine learning and big data technologies. Currently, he is working at PRTTL, Washington University in St. Louis, Saint Louis, MO, USA. 

Dr. Lalit Mohan Goyal has completed Ph.D. from Jamia Millia Islamia, New Delhi, in Computer Engineering, M.Tech. (Honours) in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi, and B.Tech. (Honours) in Computer Engineering from Kurukshetra University, Kurukshetra. He has 16 years of teaching experience in the area of theory of computation, parallel and random algorithms, distributed data mining & cloud computing. He has completed a project sponsored by Indian Council of Medical Research, Delhi. He has also published research papers in SCI indexed & Scopus indexed journals and conferences. He is areviewer of many reputed journals & conferences also. Presently, he is working at J. C. Bose University of Science & Technology, YMCA, Faridabad, in the Department of Computer Engineering.

Dr. Mamta Mittal graduated in Computer Science & Engineering from Kurukshetra University Kurukshetra in 2001 and received master’s degree (Honours) in Computer Science & Engineering from YMCA, Faridabad. She has completed her Ph.D. from Thapar University Patiala in Computer Science and Engineering. She has been teaching from the last 16 years with emphasis on data mining, machine learning, soft computing and data structure. She is a lifetime member of CSI. She has published and communicated number of research papers in SCI, SCIE and Scopus indexed Journals and attended many workshops, FDPs and Seminars. She has filed two patents – one is on human surveillance system and another is on wireless copter for explosive handling and diffusing. Presently, she is working at G.B. Pant Government Engineering College, Okhla, New Delhi (under Government of NCT Delhi), and supervising Ph.D. candidates of GGSIPU (Guru Gobind Singh Indraprastha University), Dwarka, New Delhi. She is Main Editor of the Book entitled “Data Intensive Computing Application for Big Data” published by IOS Press, Netherland, and another Book entitled “Big Data Processing Using Spark in Cloud” by Springer. She is Managing Editor of International Journal of Sensors, Wireless Communications and Control Published by Bentham Science. She is working on DST approved Project “Development of IoT based hybrid navigation module for mid-sized autonomous vehicles” and Handing Pradhan Mantri YUVA project for Entrepreneur Cell Activity as Faculty Coordinator/Representative from G.B. Pant Government Engineering College. She is a reviewer of many reputed journals, chaired number of conferences and delivered invited talks.

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