Revolutionizing Medical Systems using Artificial Intelligence: A Breakthrough in Healthcare provides an overview of various machine learning and deep learning techniques, addressing the needs of patients and the necessity for medical aid at early stages of disease. The book reviews, analyzes, and compares the different methodologies utilized for the prediction and detection of diseases. In addition, it explores the possible deployment of these advancements in medical systems, from paper to practice. With the advent of technology, tele consultation, telemedicine, and mobile health care, it is now possible to provide continuous monitoring of the health of patients.
This title fulfills the needs of connected healthcare systems, providing insights into the role of Artificial Intelligence in the prognosis, diagnosis, and analysis of several diseases. It will be a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the challenging field of artificial intelligence in medical systems and diseases.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. 1. Healthcare management using artificial intelligence - p. 1 8. 2. Background and research orientation of artificial intelligence models for segmentation in medical imaging - p. 25 9. 3. Benchmark image and clinical datasets for analysis in the medical system - p. 47 10. 4. Proactive prognosis: Predicting the course of mental and neurological disorders with artificial intelligence - p. 75 11. 5. Exploring brain tumor detection through artificial intelligence - p. 93 12. 6. Empowering early detection: artificial intelligence as a tool for breast cancer diagnosis - p. 121 13. 7. Artificial intelligence based disease diagnosis using ultrasound imaging - p. 147 14. 8. Growth optimization-based stacked bidirectional long short-term recurrent neural network model for detecting breast cancer in Internet of Things healthcare environment - p. 163 15. 9. Detection of depression by utilizing late fusion of sequential actigraphy features - p. 177 16. 10. Developmental pediatrics progression matched with artificial intelligence: A growth perspective in healthcare - p. 197 17. 11. Artificial intelligence in precision oncology: advances in cancer treatment - p. 213 18. 12. Impact of artificial intelligence bias in medical systems - p. 227 19. 13. A futuristic aspect towards modern healthcare system facilitated through artificial intelligence: A comprehensive perspective - p. 245 20. 14. Satelliting traditional to smart healthcare advancement using artificial intelligence: A paradigm shift routing futuristic slant redefining - p. 265 21. 15. Welcoming the evolution of healthcare: A transformative change through artificial intelligence and robotics - p. 285 22. Index - p. 305
Revolutionizing Medical Systems using Artificial Intelligence: A Breakthrough in Healthcare provides an overview of various machine learning and deep learning techniques, addressing the needs of patients and the necessity for medical aid at early stages of disease. The book reviews, analyzes, and compares the different methodologies utilized for the prediction and detection of diseases. In addition, it explores the possible deployment of these advancements in medical systems, from paper to practice. With the advent of technology, tele consultation, telemedicine, and mobile health care, it is now possible to provide continuous monitoring of the health of patients.
This title fulfills the needs of connected healthcare systems, providing insights into the role of Artificial Intelligence in the prognosis, diagnosis, and analysis of several diseases. It will be a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the challenging field of artificial intelligence in medical systems and diseases.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. 1. Healthcare management using artificial intelligence - p. 1 8. 2. Background and research orientation of artificial intelligence models for segmentation in medical imaging - p. 25 9. 3. Benchmark image and clinical datasets for analysis in the medical system - p. 47 10. 4. Proactive prognosis: Predicting the course of mental and neurological disorders with artificial intelligence - p. 75 11. 5. Exploring brain tumor detection through artificial intelligence - p. 93 12. 6. Empowering early detection: artificial intelligence as a tool for breast cancer diagnosis - p. 121 13. 7. Artificial intelligence based disease diagnosis using ultrasound imaging - p. 147 14. 8. Growth optimization-based stacked bidirectional long short-term recurrent neural network model for detecting breast cancer in Internet of Things healthcare environment - p. 163 15. 9. Detection of depression by utilizing late fusion of sequential actigraphy features - p. 177 16. 10. Developmental pediatrics progression matched with artificial intelligence: A growth perspective in healthcare - p. 197 17. 11. Artificial intelligence in precision oncology: advances in cancer treatment - p. 213 18. 12. Impact of artificial intelligence bias in medical systems - p. 227 19. 13. A futuristic aspect towards modern healthcare system facilitated through artificial intelligence: A comprehensive perspective - p. 245 20. 14. Satelliting traditional to smart healthcare advancement using artificial intelligence: A paradigm shift routing futuristic slant redefining - p. 265 21. 15. Welcoming the evolution of healthcare: A transformative change through artificial intelligence and robotics - p. 285 22. Index - p. 305
