Advancing Healthcare Through Data-Driven Innovations

1. Auflage 2024
ISBN: 978-1-032-73717-1
Verlag: CRC Press

Buch, Englisch, 206 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 467 g

The book emphasizes the role of data in driving healthcare transformation, providing readers with a roadmap for understanding and effectively implementing data-driven innovations. It delves into the applications of big data analytics, unveiling valuable insights and offering real-time decision support to healthcare professionals and goes on to review the role of machine learning and artificial intelligence in enabling accurate diagnosis, personalized treatment recommendations, and predictive modeling.

The book is an invaluable resource for healthcare professionals, researchers, policymakers, and technology enthusiasts alike. Its practical insights and perspectives empower stakeholders to leverage data-driven technologies effectively, thus fostering continuous improvements in patient care and shaping a brighter future for the healthcare industry as a whole.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Rehani, Gunjan

Gupta, Aditya

Jain, Vibha

Fachgebiete

• Rechtswissenschaften Öffentliches Recht Staats- und Verfassungsrecht
• Mathematik | Informatik EDV | Informatik Technische Informatik
• Rechtswissenschaften Öffentliches Recht Verwaltungsrecht Allgemeines Informationsrecht, Datenschutzrecht
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Preface. Big Data’s Impact on Healthcare Transformation. Artificial Intelligence and Machine Learning Approaches for Healthcare. Predictive Analytics Tools and Techniques for Disease Prevention and Early Detection in Healthcare Sector. Machine Learning-Based Analysis for Detection of Pancreatic Adenocarcinoma Using Urinary Biomarkers. Gland Segmentation in Colon Histology Images Using Deep Learning Method. Comparative Analysis for Detecting Cancer in Various Organs using Cellular Automata based Segmentation Technique. Convolutional Neural Networks and Transfer Learning for Medical Image Analysis: A Comprehensive Review. Multi-Objective Optimisation Enabled Improved Feature Selection. IoT-Blockchain in Remote Pregnancy Care Coordination. Strengthening Healthcare Data Security and Privacy. The Future of Healthcare: Data-driven Trends and Innovation. Index.

Über Autor(innen)

Dr. Gunjan is an Assistant Professor at the National Institute of Technology, Delhi, India. She received her Bachelor's in Technology in 2012 from Maharishi Dayanand University, Haryana, India, and her Masters in Technology from the National Institute of Technology, Jalandhar, India, in 2014. She has completed her Ph.D. in Computer Science and Engineering from the National Institute of Technology, Delhi, India. Her research interests lie in the domains of Energy techniques in Wireless Sensor Networks, Machine Learning, and Health Informatics.

Dr. Aditya Gupta is an Assistant Professor at Thapar Institute of Engineering and Technology, Patiala, Punjab, India known for his research in big data analytics, machine learning, health informatics, and blockchain. He has completed his doctoral studies at Dr B R Ambedkar National Institute of Technology, Jalandhar, India. He has published several papers in reputable international journals and completed many government-sponsored research projects. Dr. Gupta's work has significantly impacted various sectors, particularly in healthcare, where he has developed advanced health informatics systems. His expertise and dedication to research have earned him recognition as an accomplished academic and mentor.

Dr. Vibha Jain is an Assistant Professor at Thapar Institute of Engineering and Technology in Patiala, Punjab, India. She completed her Ph.D. from Netaji Subhas University of Technology in New Delhi and her Master of Technology from the National Institute of Technology in Hamirpur, India, in 2018, where she was a gold medalist. She has published papers in reputed international journals and is currently working on edge/fog computing, blockchain, and machine learning for medical diagnosis.