Full Description
Medical imaging informatics play an important role in the effectiveness of present-day healthcare systems. Advancement of artificial intelligence, big data analytics, and internet of things technologies contribute greatly to various healthcare applications. Artificial intelligence techniques are contributing to improvements with traditionally human-based systems and ensuring that the accuracy of prediction and diagnosis is being continually enhanced. The development of reliable and accurate healthcare models is becoming ever more possible with the help of machine learning and deep learning technologies. Artificial intelligence has the power to solve many complex problems in medical imaging and is a technology that will help to design the future of many healthcare systems.
This edited book highlights and addresses various issues in medical imaging and provides viable solutions utilising artificial intelligence and big data tools. This book discusses techniques, algorithms, and tools which help build and develop research practices, platforms, and applications in medical image informatics.
Medical image enhancement, big data analytics and artificial intelligence models are discussed with relation to applications in the detection of cancer, autism, allergies and diabetes. The design and development of internet of medical things and virtual reality tools for mental health disorders are also explored.
This book is suitable reading for researchers and scientists, in both academia and industry, working in computer science and engineering, machine learning, image processing, and healthcare technologies. Those in aligned professions, such as healthcare practitioners, administrators, designers and developers may also find the subject matter of interest.
Contents
Section 1: Medical image analysis using artificial intelligence
Chapter 1: Intervention of medical images for disease prediction
Chapter 2: Breast cancer detection in pathological imaging using deep learning methods
Chapter 3: Detection of autism spectrum disorder using artificial intelligence
Chapter 4: Lossless medical image compression and noise removal using deep learning models
Chapter 5: Prediction of diabetes using voting classification algorithms
Chapter 6: Use of deep learning approaches for the prediction of diseases from medical images
Chapter 7: Deep learning approach for the prediction of diseases in medical images
Chapter 8: Detection of food allergy using deep learning
Section 2: Use of AI-enabled IoT in healthcare
Chapter 9: Design and development of Internet of Things and artificial intelligence-based medical imaging system
Chapter 10: Internet of Things and medical imaging AI systems
Chapter 11: Role of artificial intelligence in medical IoT devices
Section 3: Applications of artificial intelligence in healthcare
Chapter 12: Internet automation indulgence of virtual reality in psychiatric health disorder
Chapter 13: Role of big data analytics in healthcare systems
