Khan A. Explainable Artificial Intelligence in Medical Imaging 2025 torrent

Textbook in PDF format

Artificial intelligence (AI) in medicine is rising, and it holds tremendous potential for more accurate findings and novel solutions to complicated medical issues. Biomedical AI has potential, especially in the context of precision medicine, in the healthcare industry’s next phase of development and advancement. Integration of AI research into precision medicine is the future; however, the human component must always be considered.
Explainable Artificial Intelligence in Medical Imaging: Fundamentals and Applications focuses on the most recent developments in applying artificial intelligence and data science to health care and medical imaging. Explainable artificial intelligence is a well-structured, adaptable technology that generates impartial, optimistic results. New healthcare applications for explicable artificial intelligence include clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. This book overviews the principles, methods, issues, challenges, opportunities, and the most recent research findings. It makes the emerging topics of digital health and explainable AI in health care and medical imaging accessible to a wide audience by presenting various practical applications.
Presenting a thorough review of state-of-the-art techniques for precise analysis and diagnosis, the book emphasizes explainable artificial intelligence and its applications in healthcare. The book also discusses computational vision processing methods that manage complicated data, including physiological data, electronic medical records, and medical imaging data, enabling early prediction.
Preface
Explainable Artificial Intelligence in Medicine: Social and Ethical Issues
Explainable AI for Diagnosis of Pneumonia Using Chest X-ray Images: Current Achievements and Analysis on Benchmark Datasets
Explainable AI for Medical Science: A Comprehensive Survey, Current Challenges, and Possible Directions
Explainable Artificial Intelligence Techniques in Healthcare Applications
Automatic Detection of Leukemia through Explainable AI-Based Machine Learning Approaches: Directional Review
Improvement Alzheimer’s Segmentation by VGG16 and U-Net Autoencoder Techniques
Skin Cancer Detection and Classification Using Explainable Artificial Intelligence for Unbalanced Data: State of the Art
Enhancing Heart Disease Diagnosis with XAI-Infused Ensemble Classification
Transparency in HealthTech: Unveiling the Power of Explainable AI
Therapeutic Virtual Reality Exposure Therapies for Nyctophobia and Claustrophobia with Active Heart Rate Monitoring
Explainable Artificial Intelligence-Based Machine Analytics and Deep Learning in Medical Science
Revolutionizing Prostate Cancer Diagnosis: Vision Transformers with Explainable Artificial Intelligence to Accurate and Interpretable Prostate Cancer Identification