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Full Description
Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field.
This book will be beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field.
Contents
1. Artificial intelligence in cancer research and precision medicine
2. Machine learning in computational pathology through self-supervised learning and vision transformers
3. Artificial intelligence in small-molecule drug delivery
4. AI/ML and drug repurposing in lung cancer: State of the art and potential roles for retinoids
5. Artificial intelligence and digital worlds: New frontiers of integration between AI and other technological tools
6. The dual path of the technology acceptance model: An application of machine learning cardiotocography in delivery rooms
7. Artificial intelligence in diagnostic and predictive pathology
8. Artificial intelligence in the oncology workflow: Applications, limitations, and future perspectives
9. SOK: Application of machine learning models in child and youth mental health decision-making
10. Cancer detection in hyperspectral imagery using artificial intelligence: Current trends and future directions
11. Global research trends of Artificial Intelligence and Machine Learning applied in medicine: A bibliometric analysis (2012-2022)
12. Ethics and regulations for AI in radiology
13. The role of artificial intelligence in radiology and interventional oncology
14. The multiomics revolution in the era of deep learning: Allies or enemies?
15. Artificial intelligence in behavioral health economics: Considerations for designing behavioral studies
16. Artificial intelligence and medicine: A psychological perspective on AI implementation in healthcare context
17. AI for outcome prediction in Radiation Oncology: The present and the future
18. Artificial intelligence in neurologic disease
19. Should I trust this model? Explainability and the black box of artificial intelligence in medicine
