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Feb. 10, 2026, 12:24 a.m.
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SOURCE: Gupta S. Artificial Intelligence in Healthcare. Trends, Applications,...2026
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COVER
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MEDIAINFO
Textbook in PDF format
This comprehensive book brings together a diverse collection of insights from experts in medicine, Computer Science, and data analytics to explore the evolving role of Artificial Intelligence (AI) in the healthcare sector. The chapters delve into various facets of AI applications, from legal considerations and mathematical foundations to the practical implementations of Machine Learning and Deep Learning in healthcare.
This volume is designed to bridge the gap between the technical intricacies of AI and the real-world implications for healthcare professionals, researchers, and policymakers. Our collective aim is to provide readers with a multidimensional understanding of how AI is transforming healthcare, shaping the present, and guiding the future of medical practices.
The structure of the book is organized into several parts, each addressing crucial aspects of AI in healthcare. We begin with an exploration of the challenges and future scope of AI in healthcare systems, followed by a review of the mathematical foundations and big data that form the basis of AI applications. The subsequent parts cover data processing and collection, AI application in diagnosis and treatment, imaging and disease detection, robotics, automation, and virtual worlds in healthcare, pharmaceutical and biomedical applications, ethical considerations, and finally, future trends and directions.
In recent years, biomedical sectors have been evidenced by the vast growth of AI-based technology and Deep Learning platforms, which are the future of different tools. We have highlighted herein trending AI-powered tools and Deep Learning platforms emerging in the biomedical field:
TensorFlow
Open-source software library for ML and AI developed by Google
Data analysis, image recognition, and NLP in the biomedical field
PyTorch
Open-source ML library developed by Facebook
Training neural networks, NLP, and image classification
Keras
Open-source software library that provides a Python interface for artificial neural networks
Image recognition and NLP
MatLAB
Programming language and interactive environment
Data analysis, signal processing, and ML
Scikit-learn
Open-source ML library for Python
Data analysis, classification, and regression
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