Call for papers – Intelligence-Based Medicine (IBMED)

Intelligence-Based Cardiology

Short title: IB-Cardiology

 

Cardiovascular medicine is at the forefront of clinically applied artificial intelligence (AI), with major developments in image segmentation, signal processing, big data and predictive analytics. Every month more and more academic institutions are joining the worldwide effort to develop algorithms intended to improve workflows, quality of care and ultimately clinical outcomes for the well-being of patients with confirmed or suspected cardiovascular conditions.

Successful cultivation of AI requires a close collaboration among computer scientists, clinical investigators, clinicians, engineers, administrators, and other knowledge users to co-define and solve the most relevant problems with the most efficient approaches. Collaborative experiences have highlighted a gap between the technological and scientific advances related to digital health and machine learning, and the clinical needs and understanding by clinicians and scientists unfamiliar with AI. To close this gap, faster dissemination and higher visibility is needed for work related to AI in the cardiovascular arena, especially given the exponential growth of publications in the field.

This issue invites submissions on a range of topics related to AI in cardiovascular medicine, which include but are not limited to computer vision, ECG, Doppler and other raw signal processing (to insert more topics), as well as work related to big data and analytics. Also invited are conceptual articles addressing challenges in the design, conduction and analysis of AI studies including cognitive bias, selection bias and spectrum bias, and studies addressing the complexity of implementing AI in clinical practice.

Publication Schedule

Submission portal is open for manuscript submissions: March 2021 to 15 August 2021

The expected publication date: November 2021

Special Issue Guest Editors

Francisco Lopez-Jimenez, M.D., M.Sc
Chair, Division of Preventive Cardiology
Co-Director, Artificial Intelligence in Cardiology
Director of Research, Dan Abraham Healthy Living Center
Professor of Medicine, Mayo Medical School, Mayo Clinic, Rochester
Consultant, Department of Cardiovascular Diseases
[email protected]

Louise Sun, MD, SM, FRCPC, FAHA
Director of Big Data and Health Informatics Research, University of Ottawa Heart Institute
Associate Professor of Anesthesiology and Epidemiology
Clinical Research Chair in Big Data and Cardiovascular Outcomes
University of Ottawa
Adjunct Scientist, Institute for Clinical Evaluative Sciences

Rob Brisk, MBBCh, MRCP
Clinical Research Fellow
Dept of Cardiology, Southern HSC Trust
School of Computing, Ulster University

Jai Nahar, MD, MBA
Clinical Associate Professor of Pediatrics,
George Washington University School of Medicine,
Division of Cardiology at Children’s National Hospital, Washington DC,
MBA in Health Care Management from Johns Hopkins Carey Business School,
Member of American College of Cardiology’s Health Care Innovation Section leadership council

Submit papers here