* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Artificial Intelligence for Cardiovascular Disease
Shivam Rajput, Rishabha Malviya, Deepa Muthiah, et al.
* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Naturwissenschaften, Medizin, Informatik, Technik / Klinische Fächer
Beschreibung
"e;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."e;-From the Foreword by Dr. Dhruv Galgotia, CEO-Galgotias University, IndiaToday, 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.
