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Technological advancements have enhanced all functions of society
and revolutionized the healthcare field. Smart healthcare
applications and practices have grown within the past decade,
strengthening overall care. Biomedical signals observe
physiological activities, which provide essential information to
healthcare professionals. Biomedical signal processing can be
optimized through artificial intelligence (AI) and machine learning
(ML), presenting the next step towards smart healthcare. AI-Enabled
Smart Healthcare Using Biomedical Signals will not only cover the
mathematical description of the AI- and ML-based methods, but also
analyze and demonstrate the usability of different AI methods for a
range of biomedical signals. The book covers all types of
biomedical signals helpful for smart healthcare applications.
Covering topics such as automated diagnosis, emotion
identification, and frequency discrimination techniques, this
premier reference source is an excellent resource for healthcare
administration, biomedical engineers, medical laboratory
technicians, medical technology assistants, computer scientists,
libraries, students and faculty of higher education, researchers,
and academicians.
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