A ground-breaking compilation that focuses on the integration of artificial intelligence and machine learning applications in cardiovascular healthcare... Offers helpful insights into the enormous potential of AI to change the landscape of cardiovascular care, from basic AI concepts to the most recent developments in AI-assisted wearables and diagnostic imaging.
From the Foreword by Dr. Dhruv Galgotia, CEOGalgotias University, India
Today, the need for effective and cutting-edge methods of diagnosis, treatment, and prevention of cardiovascular diseases is greater than ever before. Integrating deep learning and artificial intelligence into digital healthcare and medical environments has the potential to revolutionize cardiovascular health. The new book addresses this need by discussing emerging uses of artificial intelligence and machine learning in the prediction, diagnosis, treatment, and management of cardiovascular diseases. It looks at AI in wearable technology, nuclear cardiac imaging, coronary CT angiography, and non-contrast cardiac CT methods. It also explores the application of machine learning techniques in predicting and diagnosing cardiovascular diseases, revealing the potential for data-driven predictions and decisions that can improve patient outcomes. It explores the potential of AI in a variety of cardiology applications, including the classification of ECG signals, wearables with AI support, speech technologies in clinical settings, and more.
Discusses use of nanoparticles as nanofertifilizers and their applications in agricultural science. Summarizes research and importance of nanotechnology in abiotic stress tolerance in crop plants, its various applications in crop growth enhancement under different stress conditions, and the uses of various nanoparticles.
1. Introduction to Artificial Intelligence and Its Role in
Cardiovascular Disease
2. Artificial Intelligence Assisted Wearables for
Cardiovascular Disease Monitoring
3. Imaging Biomarkers for Cardiovascular
Disease and the Role of AI
4. Artificial Intelligence and Machine Learning
for the Treatment of Cardiovascular Disease
5. Advancement in Treatment of
Cardiovascular Disease by AI and Future Perspectives
6. AI-Based Methods and
Their Applications for the Diagnosis and Detection of Cardiovascular Disease
7. Prediction of Cardiovascular Disease Using AI
Rishabha Malviya, PhD, is an Associate Professor of Pharmacy in the School of Medical and Allied Sciences, Galgotias University, India. He has authored over 200 papers in national and international journals and published over 55 patents. He has edited over 45 books and authored more than 30 book chapters. He has been included in the Stanford Universitys Worlds Top 2% Scientists, 2020 by Elsevier BV and Stanford University. He was an invited author for the magazine Atlas of Science as well as a pharma magazine dealing with the B2B industry, Ingredients South Asia.
Shivam Rajput, MPharm, completed his bachelors in Pharmacy at Pt. B. D. Sharma University of Health Sciences, Rohtak, and his masters at Galgotias University, Greater Noida, India. He has presented many papers in national and international conferences. He has also authored six SCI/Scopus papers with a more than 10 cumulative impact factor.
Deepa Muthiah, MBBS, is an Assistant Professor of Cardiovascular Technology at Galgotias University, India. She has previously worked as a Resident Medical Officer at Chettinad Medical Centre, VIT Vellore Campus, and VIT, Vellore Campus, India. In addition, she has gained international experience as a Senior House Officer (Accident & Emergency) at King George Hospital in Essex, UK. Her innovative work has led to the filing of patents, including "Cerbro Ondular Transferring Device, co-developed with colleagues, as well as the "Smart COVID Mask," a collaborative effort with several other researchers.
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