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Machine Learning in Cardiovascular Medicine

  • ID: 4991122
  • Book
  • November 2020
  • Region: Global
  • 365 Pages
  • Elsevier Science and Technology
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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. While the industrial applications of ML are nearly ubiquitous, its introduction into the medical field has been much more gradual. The landscape, however, is rapidly changing with the availability of computational power and the creation of large repositories of datasets.

  • 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
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1. Technological Advances within Digital Medicine 2. An Overview of Artificial Intelligence: Basics and State-of-the-art Algorithms 3. Machine Learning for Predictive Analytics 4. Deep Learning for Biomedical Applications 5. Generalized Adversarial Networks (GANs) 6. Natural Language Processing 7. Contemporary Advances in Medical Imaging 8. Ultrasound and Artificial Intelligence 9. Computed Tomography and Artificial Intelligence 10. Magnetic Resonance Imaging and Artificial Intelligence 11. Nuclear Imaging and Artificial Intelligence 12. Multimodal Imaging Application of Artificial Intelligence 13. Radiomics and Precision Medicine 14. Automated Interpretation of Electrocardiographic Tracings 15. Application of Machine Learning to Genomics, Proteomics, and Cardiovascular Drug Discovery 16. Wearable Devices and Machine Learning Algorithms for Health Assessment 17. Future of Artificial Intelligence and Healthcare 18. Ethical and Legal Challenges

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Al'Aref, Subhi Jamal
Dr. Subhi Al'Aref is an Instructor in Medicine and an Instructor of Medicine in Radiology at Weill Cornell Medicine and an Assistant Attending Physician at the NewYork-Presbyterian Hospital. Dr. Al'Aref was born and raised in Jerusalem, where he finished his primary and secondary education. He subsequently performed his premedical and medical training at Weill Cornell Medical College in Qatar, and earned his M.D. in 2008. He completed his training in Internal Medicine Residency, Cardiovascular Disease Fellowship, Interventional Cardiology and Preventative Cardiology at The NewYork-Presbyterian Hospital/Weill Cornell Medicine in New York City. He is board certified in Internal Medicine, Cardiovascular Disease, Interventional Cardiology, Vascular Medicine, Echocardiography and Nuclear Cardiology.
Singh, Gurpreet
Dr. Gurpreet Singh is a Cognitive Software Engineer at Weill Cornell Medicine based in New York. He obtained his bachelor's degree in Biotechnology in 2012 and have received a scholarship to pursue his PhD at National University of Singapore, where his research project focused Machine Learning based Clinical Decision Support System for Neurodegenerative Diseases (MCADS-ND). His current work includes developing a neural network based algorithm for End-to-End echocardiogram segmentation and analysis, as well as developing a standalone software for simplified machine learning interface (SimplyClassify).
Baskaran, Lohendran
Dr. Lohendran Baskaran is a Visiting Assistant Professor of Research in Radiology at Weill Cornell Medicine, New York, and is a Consultant Cardiologist with the Department of Cardiology at the National Heart Centre Singapore. Dr. Baskaran obtained his MBBS and his BSc in Medical Physics from University College London and performed his initial medical training and MRCP in London. Currently, he is actively involved in research, teaching and clinical duties, where his research focuses on non-invasive cardiac imaging, specifically cardiac CT and Nuclear Cardiology. As an advocate for cardiac wellbeing, he fundraises for research and patients in need, and was co-chair of the inaugural NHCS Heart to Heart Gala. He is also a certified Exercise Specialist with accreditation from the American College of Sports Medicine.
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