Artificial Intelligence in Cancer Diagnosis and Prognosis: Lung and kidney cancer (Volume 1) (Physics and Engineering in Medicine and Biology, Volume 1) (Original Publisher)

Part of the authoritative Physics and Engineering in Medicine and Biology series, Artificial Intelligence in Cancer Diagnosis and Prognosis: Lung and Kidney Cancer (Volume 1) (1st Edition, 2022) presents an in-depth exploration of artificial intelligence (AI) applications in two of the most deadly cancers globally. This volume combines technical innovation with clinical relevance, providing a robust overview of machine learning, deep learning, and data-driven models in cancer imaging, pathology, and prognostic analysis.

Target Audience:
Ideal for:

• Biomedical and clinical engineers innovating AI-based diagnostic systems
• Oncologists, pulmonologists, and nephrologists seeking AI-enhanced clinical tools
• Medical imaging professionals and radiologists using AI for pattern recognition
• AI researchers and healthcare data scientists focusing on oncology applications
• Graduate students and academic professionals in biomedical informatics and computational medicine

Key Features and Highlights:

• Covers AI techniques in lung and kidney cancer detection, staging, and prognosis
• Integrates imaging, histopathological, and genomic data for multi-modal analysis
• Explores supervised and unsupervised learning models in real-world diagnostic settings
• Reviews clinical trial outcomes, data validation challenges, and AI limitations
• Discusses regulatory, ethical, and translational aspects of implementing AI in oncology
• Written by a global team of experts in AI, medical physics, and cancer research

Topics Covered:
Includes core chapters on:

• Deep learning for radiographic and CT image interpretation
• Predictive modeling for cancer survival and treatment response
• Integration of clinical and molecular data using AI frameworks
• Data preprocessing, annotation, and algorithm training
• AI applications in low-resource settings and global cancer care

About the Author:
Authored and edited by an interdisciplinary team of professionals in artificial intelligence, medical imaging, and clinical oncology, this volume reflects the most current advances from both research and practice in AI-powered cancer diagnostics.

File Format & Technical Specifications:

• Available Formats: PDF
• File Size: Approximately 8–12 MB
• Language: English
• Device Compatibility: Compatible with all major e-readers (Kindle, Kobo), tablets, laptops, and smartphones supporting PDF

FAQs:

1. How technical is this book—do I need a programming or AI background to benefit from it?
While it includes technical content, the book balances conceptual explanations with practical examples, making it suitable for both technical professionals and clinicians looking to understand AI applications in cancer care.

2. Does the book include discussions on data sources and validation?
Yes, it features important considerations around data acquisition, annotation, model validation, and clinical translation, especially in the context of real-world diagnostic use.