AI and Precision Oncology

Innovations in Diagnosis and Drug Development

Häftad, Engelska, 2026

1 666 kr

Kommande

Beskrivning

AI and Precision Oncology: Innovations in Diagnosis and Drug Development examines the transformative role of artificial intelligence and machine learning in oncology. This book addresses the urgent need for early cancer diagnosis and effective therapeutic treatments, highlighting how technological advancements enable rapid analysis of large datasets to enhance patient outcomes. The content explores clinical applications of next-generation sequencing (NGS) integrated with AI technologies, covering risk prediction, disease detection, biomarker identification, and therapeutic target discovery. It emphasizes the importance of bioinformatics tools in analyzing NGS data and showcases AI-powered applications that improve cancer diagnosis and prognostication. For the academic audience, this book provides valuable insights into the latest advancements in AI and precision oncology. It equips researchers and clinicians with knowledge on personalized treatment strategies and recent clinical studies, ultimately enhancing understanding of how AI can revolutionize cancer care and improve patient management.

Provides an in-depth exploration of how artificial intelligence and machine learning are integrated into various aspects of oncology, including diagnosis, treatment planning, and patient management
Emphasizes the critical role of next-generation sequencing technologies in precision oncology, detailing their applications in risk prediction, biomarker identification, and therapeutic target discovery
Highlights how AI-driven tools can assist in tailoring personalized treatment options based on genetic, environmental, and lifestyle factors

Produktinformation

Utgivningsdatum:2026-11-01
Mått:191 x 235 x undefined mm
Vikt:450 g
Format:Häftad
Språk:Engelska
Antal sidor:350
Förlag:Elsevier Science
ISBN:9780443445835

Utforska kategorier

Biologi inom Naturvetenskap och teknik

Mer om författaren

Arun Kumar Singh is an Assistant Professor in the Department of Pharmacy at University School of Pharmaceutical Sciences, Rayat Bahra University V.P.O. Sahauran , India. He completed his M.Pharm in Pharmaceutics from Galgotias University, Greater Noida. His research interests include nano-formulation, blockchain, IoT, machine learning, artificial intelligence, big data analytics, cancer biology, and neuroscience. He has contributed to academic books and book chapters and has published review articles in the areas of pharmaceutical sciences and healthcare technology. His work focuses on interdisciplinary approaches integrating pharmaceutical research with emerging digital and computational technologies. Prateek Agrawal is professor and deputy dean at the School of Computer Science & Engineering, Lovely Professional University, Phagwara, Punjab, India. His research areas include natural language processing, computer vision, video processing, expert systems, deep learning applications, and other related topics. He is a senior member of IEEE and core member of IEEE India Council for Sustainable Development Activity, and is also a member of different reputed organizations like IET, MIR lab, and IAENG among others. Dr. Agarwal has published over 70 research papers in Scopus/SCIE indexed journals and conferences, 60 national patents, five edited books, and 10 book chapters. He is book series editor of the IOP series on next generation computing, and is a reviewer for many SCIE journals like Multimedia tools and Applications, Plos One, PeerJ, Oxford computer science, IEEE Access, and Ambient Intelligent & Humanized Computing.Dr. Niraj Kumar Jha is an Assistant Professor of Biotechnology at Galgotias University, India, with prior research affiliations at the Centre for Research Impact & Outcome (CRIO), Chitkara University, and Sharda University. His research portfolio encompasses over 200 peer-reviewed articles and scholarly reviews, along with an edited volume published by Springer, reflecting sustained contributions to biomedical research and translational science. According to Scopus metrics, Dr. Jha’s publications have garnered more than 10,000 citations, with an H-index exceeding 50, underscoring the broad impact and visibility of his work within the global scientific community. He is an elected Member of the Royal Society of Biology (MRSB), London, and has been recognized among the World’s Top 2% Scientists in rankings compiled by Elsevier in collaboration with Stanford University. Dr. Jha actively contributes to scientific publishing and peer review as an associate editor for the Journal of Alzheimer’s Disease (IOS Press) and IET Nanobiotechnology (Wiley) and serves on the editorial boards of several international journals, including Scientific Reports. His research is centered on elucidating the molecular and cellular mechanisms underlying complex diseases such as neurodegenerative disorders, cancer, and cardiovascular pathologies. His work particularly emphasizes the modulation of key signaling pathways and explores the therapeutic potential of natural products, phytochemicals, and synthetic small molecules in disease intervention.

Innehållsförteckning

1. Artificial Intelligence Applications in Clinical Oncology: A Comprehensive Overview2. Artificial Intelligence Tools in Cancer Diagnosis and Treatment3. The Role of Machine Learning in Personalized Cancer Care4. The Role of Artificial Intelligence in Advancing Digital Pathology for Oncology5. Transformative Applications of Artificial Intelligence in Digital Pathology: Bridging the Gap Between Research and Clinical Practice6. Imaging in Neuro-Oncology: Clinical Uses of Radiomics and Artificial Intelligence7. AI-Driven Digital Histopathology: Revolutionizing Prognostication and Treatment Efficacy in Cancer Care8. Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine9. Precision Oncology and Immune Therapy with the Use of AI and Digital Biomarkers in Precision Pathology10. Evaluating Artificial Intelligence's (AI) Significance in Clinical Oncology: Practical Applications of Machine Learning for Radiotherapy11. Regulatory Pathways for AI in Cancer Therapy12. Challenges Associated with AI in Cancer Therapy13. Current and Future Applications of Artificial Intelligence in Cancer Pathology: A Clinical Perspective