About Book:
Bentham Science announces the publication of a new book, "Deep Learning for Healthcare Services," which represents a transformative leap in the integration of deep learning technologies within the healthcare industry. This comprehensive resource unlocks the potential of artificial intelligence to revolutionize healthcare delivery and improve patient outcomes.
Deep learning, a branch of artificial intelligence (AI), falls within the broader realm of machine learning. It centers on empowering computers to learn from data and autonomously make decisions or predictions, eliminating the need for explicit programming. These advanced algorithms in deep learning are crafted to represent intricate patterns and high-level concepts in data, employing artificial neural networks that draw inspiration from the intricate structure and functioning of the human brain.
Authored by a team of esteemed experts in the fields of artificial intelligence and healthcare, "Deep Learning for Healthcare Services" is a cutting-edge guide that explores the convergence of deep learning algorithms, medical data, and healthcare applications. This eBook is designed to equip healthcare professionals, researchers, and technology enthusiasts with the necessary knowledge to leverage deep learning techniques and reshape the future of healthcare.
This book highlights the applications of deep learning algorithms in implementing big data and IoT enabled smart solutions to treat and care for terminally ill patients. It presents 5 concise chapters showing how these technologies can empower the conventional doctor patient relationship in a more dynamic, transparent, and personalized manner. The key topics covered in this book include:
- The Role of Deep Learning in Healthcare Industry: Limitations
- Generative Adversarial Networks for Deep Learning in Healthcare
- The Role of Block-chain in the Healthcare Sector
- Brain Tumor Detection Based on Different Deep Neural Networks
Key features include a thorough, research-based overview of technologies that can assist deep learning models in the healthcare sector, including architecture and industrial scope. The book also presents a robust image processing model for brain tumor screening.
Through this book, the editors have attempted to combine numerous compelling views, guidelines and frameworks. Healthcare industry professionals will understand how Deep Learning can improve health care service delivery.
For more information about the book or to acquire a copy, please visit https://bit.ly/3pOcbpB
About the Authors:
Dr. Parma Nand, with a PhD in Computer Science & Engineering from IIT Roorkee, possesses 27+ years of experience in industry and academia. Recognized for excellence, he received awards for teaching, Microsoft's best students project guide in 2015, and Cognizant's best faculty in 2016. He has led successful government-funded projects and spearheaded notable IEEE conferences and events.
Dr. Vishal Jain, an Associate Professor at Sharda University, Greater Noida, U.P., has over 14 years of academic experience. He holds a Ph.D., M.Tech, MBA, MCA, MCP, and CCNA, with 370+ research citations on Google Scholar (h-index 9, i-10 index 9).
Dac-Nhuong Le (Lê Đắc Nhường) has an M.Sc. and Ph.D. in computer science from Vietnam National University, Vietnam in 2009 and 2015, respectively. He is an Associate Professor of Computer Science, and the Dean of the Faculty of Information Technology at Haiphong University, Vietnam. He has a total academic teaching experience of 15+ years with many publications in reputed international conferences, journals, and online book chapter contributions (Indexed by SCI, SCIE, SSCI, Scopus, ACM, DBLP).
Jyotir Moy Chatterjee is working as an Assistant Professor in the Department of Information Technology at Lord Buddha Education Foundation (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal, having H-index 22.
Dr. Ramani Kannan is Senior Lecturer and Postgraduate Programme Leader in the Department of Electrical and Electronics Engineering at Universiti Teknologi PETRONAS, Malaysia and Chair, IEEE PELS, Malaysia Chapter since 2022. With an outstanding record spanning over 17 years in teaching, 15 years in research and development, and 14 years in academic administration, Dr. Ramani has established himself as a prominent figure in the field.
Dr. Vishal Jain holds a B.Tech (IT), M.Tech (CSE), and a Ph.D. (CSE). His teaching excellence has been recognized with awards at I.TS Engineering College, Gr. Noida, and ABESIT, Ghaziabad. He has published five research papers in international journals and conferences, and his expertise spans Software Engineering & Testing, DBMS, Cyber Security, and Pattern Recognition. Dr. Jain has organized sponsored Faculty Development Programs and various workshops, guest talks, and seminars at I.T.S Engineering College, Gr. Noida.