Handbook of AI-Based Models in Healthcare and Medicine

ISBN-13: 9781032419152 / Twarda / 2024 / 512 str.

Opis

This handbook provides thorough, in-depth, and well-focused developments of AI, ML, DL, NLP, cryptography, and Blockchain approaches along with their applications focused on healthcare systems.

Spis treści

1. Edge Computing with IoT devices in Healthcare: Concepts, Tools, Techniques, and Use cases.

Shalini Ramanathan, Anabel Pineda-Briseno, Tauheed Khan Mohd and Mohan Rama Sundaram

2. History and Role of AI in Healthcare and Medicine.

Dipali Dakhole, and Praveena Khushal rao

3. Drug Discovery using Explainable AI Approaches: The Current Scenario.

Chinju John, Akarsh K Nair, Jayakrushna Sahoo

4. Supervised Learning Models for Diagnosing Severity of Cirrhosis Disease.

Akshita Sakshi, J.V. Bibal Benifa, P. Antony Seba

5. 3D Volumetric Computed Tomography from 2D X-rays: A Deep Learning Perspective.

Manish Kumar, Suman Kumar Maji, Hussein Yahia

6. GAN based Encoder Decoder Model for Multi-label Diagnostic Scan Classification and Automated Radiology Report Generation.

Rahul Kumar, Karthik K, Sowmya Kamath S

7. A Survey of Machine Learning and Deep Learning-Based Techniques for Diabetic Retinopathy Screening.

Nitigya Sambyal, Poonam Saini, Rupali Syal

8. An Embedded Solution for Real-Time Implementation of Deep learning Model for Malicious Breast Tumour Detection.

S. Malarvizhi, R. Kayalvizhi, H. Heartlin Maria, Revathi Venkatraman, Shatanu Patil, A.Maria Jossy

9. Towards Robust Diagnosis of Alzheimer’s Disease using Ensemble Framework of Convolutional Neural Network and Vision Transformer.

Poonguzhali Elangovan, and Malaya Kumar Nath

10. Retinal AlexU-Net: Segmentation of Retinal Vascular Network for the Diagnosis of Diabetic Retinopathy.

Sathya Vani A, Sumathi D

11. Decoding EEG Signals for Generating Images using GANs.

Ritik Naik, Kunal Chaudhari, Ketaki Jadhav, Amit Joshi

12. Mental Health Disorder through Electroencephalogram Analysis using Computational Model.

Kiran Waghmare, and Meenakshi Malhotrab

13. Machine Learning Techniques in ECG Data Analysis for Medical Applications.

Daphin Lilda. S and Jayaparvathy. R

14. Heartcare Assistance System: A Machine Learning based Cardiovascular Risk Monitoring Tool (CRMT).

Barath Vignesh. S, Kanishk. P, A. Kannammal, E. Chandra Blessie

15. Parameter Estimation of Real-Time NCS Signal Acquired Using Designed Neurostimulator for Developing Microcontroller-Based Healthcare Support System.

Amarprit Singh, Lachit Dutta, Anil Hazarika, Champak Talukdar, and Manabendra Bhuyan 

16. Critical Analysis of Current Healthcare Applications for Diagnosis of Diseases: Pitfalls and Future.

Tumul Vikram Singh, Qazi Amanur Rahman Hashmi, Nitu Dogra, Ankur Saxena, Deepshikha Pande Katare and Ruchi Jakhmola Mani

17. Machine Learning Based Decision Support System for Optimal Treatment of Acute Inflammation Response With Specific Patient Conditions.

Selami BEYHAN, Meriç ÇETİN 

18. Digital Histopathology: Paving Future Directions Towards Predicting Diagnosis of disease via Image Analysis.

Rishita Singh, Nitu Dogra, Ravina Yadav, Angamba Meetei Potshangbam, Deepshikha Pande Katare and Ruchi Jakhmola Mani.

19. Artificial Intelligence Techniques to design Epitope Mapped Vaccines and Diagnostics for Emerging Pathogens.

Hina Bansal and Navya Aggarwal

20. Deep Network-Based Drug Target Interaction Model To Identify Potential Drug Molecules Against COVID-19.

Santhosh Amilpur and Chandra Mohan Dasari

21. Deep Learning-based Chatbots for Patient Queries.

Priya Vijay, K. Jayashree, R. Babu, Mr. K. Vijay

22. Autism, ADHD and Dyslexia Disorder Comorbidity: An Enhanced Study on Education for Children through Artificial Intelligence-Enabled Personalized Assistive Tools.

Praveena K N, Mahalakshmi R, Mahalakshmi R, Dipali K Dakhole

O autorze

Dr. Bhanu Chander, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Graduated from Acharya Nagarjuna University, A.P, and post-graduate degree from the Central University of Rajasthan, Rajasthan. Ph.D. on Machine Learning in Wireless Sensor Networks for sensor data classification from Pondicherry University in 2022. Dr. Bhanu's primary research interests are in the area of Wireless Sensor Networks, Machine Learning and IoT security. As we know, computer science, as a field, has largely focused on problems relevant to the developed world. The Internet and the World Wide Web have remained largely urban phenomena, which mean that a significant fraction of the developing world, especially in rural and underdeveloped regions, remains disconnected from the rest of the world. Dr. Bhanu is a well-recognized academic reviewer by IEEE, ACM, and Springer, who served for 16 various scientific journals and conferences in the review process of more than 50 articles. He contributed as a track chair and session chair for numerous international conferences and workshops, and performed as a technical program committee (TPC) member for several international conferences organized by IEEE, Springer, and ACM.

He is interested in Machine Learning techniques for Energy efficient 6G Networks, Blockchain Technology for the Security of Internet of Things and Wireless Communications, Analysis and verification of cryptographic protocols, Satellite image analysis: identification of novel features or misclassified features. He published 8 articles in peer-reviewed journals, 5 international conferences, and 8 book chapters (Elsevier, Wiley, CRC and Springer). Presently his main interesting areas include Wireless Sensor Networks, IoT and Healthcare, Cryptography, Machine Learning, Deep Learning.

Dr. Anoop, working as Postdoctoral Research Fellow at Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Centre, US. He received Ph.D. degree on Development of Automated Methods for Retinal Optical Coherence Tomography Image Analysis from National Institute of Technology, Surathkal in 2021. MTech on Signal Processing from National Institute of Technology, Calicut, 2013. Best Paper Award in the 9th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2021 for the work entitled” Attention Assisted Patchwise CNN for the Segmentation of Fluids from the Retinal Optical Coherence Tomography Images”. Organized by Machine Intelligence Unit, Indian Statistical Institute (ISI), Kolkata, India on December 2021. Free graduate student non-author registration to the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC21). Research Fellow: Project entitled ”Retinal cysts identification and quantification from low SNR optical coherence tomography scans using image processing techniques”, Funding Agency: DST-SERB from May 2017 to March 2020. He has membership in professional bodies IEEE, IEEE Signal Processing, Engineering In Medicine And Biology Society, Internet Society.

He published 6 articles in peer-reviewed journals, and 2 book chapters. Presently his main interesting areas include Medical Image processing, Deep Learning, GANs and Auto-encoders.

Dr. Koppala Guravaiah, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Completed Ph.D. on the topic performance of Routing protocols in Wireless Sensor Networks using River formation dynamics from National Institute of Technology Tiruchirappalli, India. His research interests include the Internet of Things (IoT), Wireless Sensor Networks (WSN), MANETs, Applications and Security aspects in IoT, WSN, & MANETs, Natural Language Processing. He is an active speaker in various international and National conference. He contributed as a track chair and session chair for numerous international conferences and workshops, and performed as a technical program committee (TPC) member for several international conferences. He published 5 Journals, 8 conferences, 2 book chapters in the areas mentioned above by his name. He is a member in various professional research bodies such as IEEE, and ACM.

Dr. G. Kumaravelan, currently serving as Associate Professor, Department of Computer Science, School of Engineering and Technology, Pondicherry University, Karaikal Campus, Karaikal. He received his M.Tech Degree in Advanced Information Technology and Ph.D in Computer Science from Bharathidasan University, Trichy, India in the year 2009 and 2013 respectively. He has published more than 25 research papers in reputed international journals indexed in Scopus and SCI and conferences including IEEE, SPRINGER and ACM. He received two best paper awards in the International conferences organized by IITs. He has received “Best Teacher Award” by Pondicherry University, based on student’s evaluation for past six years (2013-14, 2014-15, 2015-16, 2016-17, 2017-18 and 2018-19). He has gained 17 years of rich teaching and research experience. He is an active reviewer in various international conferences and peer-reviewed journals reviewed more than 200 papers. He has acted as resource person in various FDPs, Conferences and Seminars in higher educational institutions. He contributed as a track chair and session chair for numerous international conferences and workshops, and performed as a technical program committee (TPC) member for several international conferences. His research interests include the internet of things, cloud computing, big data analytics, wireless communications, and networking.