Artificial Intelligence for Enhanced Diagnosis in Oncology explores the transformative role of AI in cancer care, examining its applications across various domains. The book introduces key AI technologies, such as machine learning and natural language processing and discusses the challenges and opportunities they present in oncology. Each chapter focuses on specific areas where AI has significant impact, including early cancer screening, diagnosis, pathology, surgical oncology, and imaging. Readers will learn how AI improves precision in treatment, optimizes clinical trial designs, and accelerates drug discovery while addressing critical issues like predicting adverse drug reactions and assessing cancer risks.
Emphasizing personalized oncology, the book also highlights innovative approaches to patient education and engagement. Concluding with insights on emerging trends and ethical considerations, this resource is essential for researchers, clinicians, and healthcare professionals committed to advancing cancer care through AI technologies.
1. Chapter 1. Artificial intelligence in oncology: An introduction - p. 1 2. Chapter 2. AI in early cancer screening - p. 23 3. Chapter 3. AI in cancer diagnosis and prognosis - p. 41 4. Chapter 4. AI-driven pathology: Transforming histopathological analysis - p. 55 5. Chapter 5. Integrating liquid biopsy and artificial intelligence for precision detection of cancer signatures - p. 69 6. Chapter 6. AI in surgical oncology - p. 85 7. Chapter 7. Artificial intelligence in cancer imaging - p. 93 8. Chapter 8. Artificial intelligence and radiomics in precision oncology - p. 111 9. Chapter 9. AI in cancer clinical trials enhancing study design and patient selection - p. 129 10. Chapter 10. AI in designing novel cancer treatments - p. 149 11. Chapter 11. Artificial intelligence for personalized oncology: Tailoring treatments to individual patients - p. 169 12. Chapter 12. Artificial intelligence in predicting adverse drug reactions, surgical outcomes, and radiotherapy responses - p. 189 13. Chapter 13. Artificial intelligence in cancer risk assessment - p. 203 14. Chapter 14. Artificial intelligence for oncology sepsis risk and mortality prediction - p. 217 15. Chapter 15. AI in cancer education and screening: Improving patient awareness and quality of life - p. 233 16. Chapter 16. The future of AI in oncology: Trends and innovations - p. 255 17. Index - p. 265
Artificial Intelligence for Enhanced Diagnosis in Oncology explores the transformative role of AI in cancer care, examining its applications across various domains. The book introduces key AI technologies, such as machine learning and natural language processing and discusses the challenges and opportunities they present in oncology. Each chapter focuses on specific areas where AI has significant impact, including early cancer screening, diagnosis, pathology, surgical oncology, and imaging. Readers will learn how AI improves precision in treatment, optimizes clinical trial designs, and accelerates drug discovery while addressing critical issues like predicting adverse drug reactions and assessing cancer risks.
Emphasizing personalized oncology, the book also highlights innovative approaches to patient education and engagement. Concluding with insights on emerging trends and ethical considerations, this resource is essential for researchers, clinicians, and healthcare professionals committed to advancing cancer care through AI technologies.
1. Chapter 1. Artificial intelligence in oncology: An introduction - p. 1 2. Chapter 2. AI in early cancer screening - p. 23 3. Chapter 3. AI in cancer diagnosis and prognosis - p. 41 4. Chapter 4. AI-driven pathology: Transforming histopathological analysis - p. 55 5. Chapter 5. Integrating liquid biopsy and artificial intelligence for precision detection of cancer signatures - p. 69 6. Chapter 6. AI in surgical oncology - p. 85 7. Chapter 7. Artificial intelligence in cancer imaging - p. 93 8. Chapter 8. Artificial intelligence and radiomics in precision oncology - p. 111 9. Chapter 9. AI in cancer clinical trials enhancing study design and patient selection - p. 129 10. Chapter 10. AI in designing novel cancer treatments - p. 149 11. Chapter 11. Artificial intelligence for personalized oncology: Tailoring treatments to individual patients - p. 169 12. Chapter 12. Artificial intelligence in predicting adverse drug reactions, surgical outcomes, and radiotherapy responses - p. 189 13. Chapter 13. Artificial intelligence in cancer risk assessment - p. 203 14. Chapter 14. Artificial intelligence for oncology sepsis risk and mortality prediction - p. 217 15. Chapter 15. AI in cancer education and screening: Improving patient awareness and quality of life - p. 233 16. Chapter 16. The future of AI in oncology: Trends and innovations - p. 255 17. Index - p. 265
