Artificial Intelligence in Gastrointestinal Cancers
by Ganji Purnachandra Nagaraju, Venkatesan Amouda, Ampasala Dinakara Rao
1st Edition
Publisher: Academic Press
Book Details
| Print ISBN | 9780443441219 |
| eText ISBN | 9780443441226 |
| Publisher | Academic Press |
| Publishing Year | 2026 |
| Edition | 1st Edition |
| Language | English |
| Pages | 332 |
Artificial Intelligence in Gastrointestinal Cancers, 1st Edition, details the application of computational methods in gastrointestinal oncology for researchers, academics, scholars, students, and clinicians. The book addresses how algorithmic systems support the evaluation and management of digestive tract malignancies. It establishes fundamental concepts behind machine learning deployment across clinical and laboratory settings.
The core material surveys diagnostic and analytical techniques. Deep learning models enhance the interpretation of medical imaging, including endoscopic, magnetic resonance imaging, and computed tomography scans. Additionally, machine learning algorithms process large clinical and omics datasets to evaluate disease prognosis, discover biological markers, and predict patient responses to therapeutic regimens.
Later chapters address therapeutic innovation, detailing methods by which artificial intelligence accelerates drug discovery, models drug repurposing, and optimizes clinical trial design. The text concludes with an evaluation of current challenges and future perspectives in the field, offering clinicians and scholars a clear overview of computational GI oncology.
Table of Contents
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
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