Full Description
Digital technologies are essential to future-proof our health service. With an ageing population and the landscape of the post-pandemic world making increasing demands on an already-stretched human workforce, maximising the potential of a digital future is necessary. This book introduces the concepts and underpinning technology behind recent developments to give a snapshot of the state of the art in the field of digital health and provides information for clinicians at all levels of experience. The reader will gain insight into digital health in general, with clinical, technical and industrial insights providing context to the theory.
Key Features
Defines the value that Artificial Intelligence (AI) brings to healthcare, resulting in improved clinical diagnosis and decision-making
Enables not just imaging staff but other healthcare practitioners to extract the best ways of working with AI using the underpinning knowledge from this text
Contents
Foreword by Susan C. Shelmerdine. Foreword by Raymond Bond. Preface. Editors' Biographies. List of Contributors. 1. Introduction and Learning Objectives. 2. Person/Patient-Centred Practice with AI: The Patient, the Practitioner and the Use of Technology to Enable Better Patient Care. 3. Background to Technology Used in Healthcare. 4. Statistical Analyses and Reporting of Performance of AI Models: An Introduction to AI Statistics. 5. Human-Computer Interaction and Biases Associated with Technology Use in the Context of Healthcare. 6. Educating Clinicians of the Future in AI. 7. Opportunities and Equity in Imaging AI: Implications for Indigenous and Underrepresented Populations. 8. AI in Cardiology. 9. AI in Radiology. 10. Artificial Intelligence in Onco-Radiology: From Promise to Practice, Industry to Implementation. 11. The Application of Artificial Intelligence to Histopathology. 12. AI in Ophthalmology. 13. AI in Dermatology: AI-Enabled Diagnostics in Dermatology - A Case Study in Skin Cancer Devices. 14. Sustainability in Clinical AI. Case Study A: Practical Implication - How to Integrate AI Responsibly into Life and Personal Health - The Hear Glue Ear Example. Case Study B: AI for Adaptive Learning - A Case Study in Personalising Mammography Education. Case Study C: Integrating Artificial Intelligence into Healthcare - The Patient's Perspective. Case Study D: Transforming Radiology Workflows at Leiden University Medical Centre (LUMC) - A Case Study in the Clinical Integration of AI for Chest X-Ray Interpretation. Index.
