The book covers diverse topics, including medical image denoising, the transformative role of GANs, IoT applications in healthcare, early disease detection using speech data, and COVID detection using autoencoders. It also explores the impact of big data, statistical approaches to medical analytics, and public health improvements through technology.
Key Features:
- Practical insights into deploying advanced machine learning models for healthcare.
- Real-world case studies on diverse diseases and datasets.
- Cutting-edge topics like explainable AI, federated learning, and ethical considerations.
- Methods for improving data accuracy, efficiency, and privacy.
Readership: Researchers, academics, graduate students, and professionals in data science, bioinformatics, and healthcare analytics.
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