AI and Data Science in Healthcare Applications by Ashwani Kumar(.PDF)+
File Size: 26.1 MB
Artificial Intelligence and Data Science in Healthcare Applications by Ashwani Kumar, Gautam Srivastava, P. K. Gupta, Mohit Kumar
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Overview: Artificial Intelligence and Data Science in Healthcare Applications provides a thorough in-depth examination of how AI and Data Science are transforming predictive analytics and outlier detection in every industry. With in-depth examinations of Machine Learning, neural networks, NLP, and ethics of AI, this book prepares readers with both theoretical principles and practical tools to create smart, scalable systems. Real-world healthcare, cybersecurity, and finance case studies exemplify real world applications, and tutorials with leading libraries serve as a starting point for implementation. Chapter 1 deals with the automated diagnosis of ADHD disease with a few state-of-the-art Artificial Intelligence algorithms. The experimental study and the results obtained after implementing advanced Deep Learning approaches to EEG signals specifically for the classification of ADHD. This research incorporates six models: Temporal Convolutional Network, Temporal Convolutional Network with Attention, Recurrent Neural Network, Graph Neural Network, CNN with GRU, and a hybrid model that has CNN, RNN, and Attention. Having a significant literature review of numer- ous relevant and recent research works along with the experimental details, this chapter can be a significant part of this book. It will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer engineering, information technology, and biomedical engineering.
Genre: Non-Fiction > Tech & Devices
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