Machine Learning in Cardiovascular Medicine is popular PDF and ePub book, written by Subhi J. Al'Aref in 2020-11-20, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Machine Learning in Cardiovascular Medicine can be Read Online from any device for your convenience.
Machine Learning in Cardiovascular Medicine Book PDF Summary
Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach
Detail Book of Machine Learning in Cardiovascular Medicine PDF
- Author : Subhi J. Al'Aref
- Release : 20 November 2020
- Publisher : Academic Press
- ISBN : 9780128202746
- Genre : Science
- Total Page : 456 pages
- Language : English
- PDF File Size : 20,5 Mb
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