Artificial Intelligence in Gastrointestinal Cancers

Ganji Purnachandra Nagaraju, Venkatesan Amouda, Ampasala Dinakara Rao

• Publisher: Academic Press
• Year: 2026
• Topic: Biological Sciences
• eBook ISBN:
  9780443441226
• Subtopic: Biology
• Index: Biological Sciences

Artificial Intelligence in Gastrointestinal Cancers examines the transformative impact of AI technologies on diagnosing and treating gastrointestinal malignancies. This book explores how advanced algorithms, particularly deep learning models, enhance the analysis of medical imaging, including endoscopic, MRI, and CT scans, facilitating earlier and more accurate identification of cancers such as esophageal, stomach, colorectal, and pancreatic cancers. The content covers AI's multifaceted applications, from improving diagnostic accuracy to personalizing treatment strategies based on genomic and clinical data. It discusses how machine learning predicts patient outcomes and optimizes treatment plans while also addressing AI's role in accelerating drug discovery and clinical trials. For an academic audience, this book provides crucial insights into AI's current and future applications in GI oncology. Readers gain a comprehensive understanding of AI diagnostic tools and personalized treatment strategies, equipping researchers and clinicians with the knowledge to leverage these advancements for improved patient care and outcomes in gastrointestinal cancers. - Provides a comprehensive overview of how AI algorithms are applied in the early detection and diagnosis of gastrointestinal cancers - Highlights the role of machine learning in analyzing large datasets to predict treatment responses and patient outcomes - Outlines how AI accelerates the process of drug discovery and optimizes clinical trial design

Table of contents

• Title of Book
• Chapter 1. Artificial intelligence in gastrointestinal cancers
• Chapter 2. The role of artificial intelligence (AI) and machine learning (ML) in gastrointestinal (GI) tract cancers: challenges and opportunities
• Chapter 3. Rise of machine learning applications in diagnosis and prognosis of gastric cancer: Imaging and omics data
• Chapter 4. Imaging to intervention: examining the potential of artificial intelligence for gastrointestinal cancers
• Chapter 5. Developments of AI based early detection and diagnosis method in pancreatic cancer
• Chapter 6. Exploring artificial intelligence approaches for studying intrinsically disorder proteins involvement in gastrointestinal cancers
• Chapter 7. Identification of diagnostic transcriptome regulatory network for prediction of early-onset Gastric Cancer using integrated bioinformatics analysis
• Chapter 8. Data to diagnosis: AI-powered insights for biomarker discovery in gastrointestinal tract cancers
• Chapter 9. The role of artificial intelligence in gastric cancer diagnosis, prognosis, surgery and drug discovery
• Chapter 10. Acceptance sampling approaches in discovering drugs for gastrointestinal cancer
• Chapter 11. Transforming gastrointestinal tract cancer with applications and advancements of artificial intelligence and machine learning: A next-generation patient care
• Chapter 12. Harnessing artificial intelligence for screening phytochemicals in gastrointestinal cancer therapeutics
• Chapter 13. Exploring AI-enabled drug discovery and repurposing approaches for gastrointestinal tract cancer
• Chapter 14. AI-driven drug repurposing strategies for hepatocellular carcinoma: Unlocking new therapeutic potential
• Chapter 15. Revolutionizing therapeutic possibilities for hepatocellular carcinoma by advanced bioinformatics and artificial intelligence-driven drug repurposing
• Chapter 16. Challenges and future perspectives of AI in gastrointestinal cancers
• Index