HeartSciences Adds Prominent Key Advisors to its Scientific Advisory Board
Southlake, TX, May 07, 2025 (GLOBE NEWSWIRE) -- HeartSciences Inc. (NASDAQ:HSCS) ("HeartSciences" or the "Company"), an artificial intelligence (AI)-powered medical technology company focused on transforming ECGs/EKGs to save lives through earlier detection of heart disease, today announced the appointment of Dr. Girish Nadkarni, MD, Dr. Joshua Lampert, MD, and Dr. Akhil Vaid, MBBS, to its Scientific Advisory Board. These appointments underscore HeartSciences' commitment to advancing and transforming data-driven AI-ECG technology.
"We are honored to welcome Dr. Girish Nadkarni, Dr. Joshua Lampert, and Dr. Akhil Vaid to our Scientific Advisory Board," said Andrew Simpson, CEO of HeartSciences. "Each of these distinguished leaders brings a wealth of expertise at the intersection of cardiology, artificial intelligence, and data-driven healthcare. Their pioneering work in clinical AI applications and digital medicine will be instrumental in advancing our mission to transform the standard of cardiac care through early detection and intervention. With their guidance, HeartSciences is better positioned than ever to lead the evolution of ECG technology into an essential diagnostic tool for a new era of precision medicine."
Dr. Girish Nadkarni, MD, MPH
Dr. Girish N. Nadkarni is a physician-scientist and clinical informaticist, whose career is marked by leadership in artificial intelligence (AI) and precision medicine. He is currently the Fishberg Professor of Medicine, the Director of the Charles Bronfman Institute for Personalized Medicine and the Inaugural System Chief of the Division of Data-Driven and Digital Medicine at the Icahn School of Medicine at Mount Sinai.
He has spearheaded transformative and translational research leading to 375 original peer-reviewed research and 55 invited publications with over 40,000 citations and an h-index of 90. These include senior authored papers in journals including New England Journal of Medicine, Journal of American Medical Association, Annals of Internal Medicine, Nature Medicine and Lancet Digital Health. His work has advanced fields including precision medicine, including landmark studies using electrocardiograms for predicting outcomes, understanding impact of predictive AI in healthcare, AI-bioprognostics for kidney disease and predictive approaches for kidney disease. Dr. Nadkarni's innovations extend to entrepreneurship, where he co-founded several companies that have pioneered AI-based approaches receiving FDA clearance. He is principal investigator for eight concurrent R01 grants or equivalents, three industry contracts and two NIH contracts for a cumulative amount of ~$40 million. Additionally, he holds numerous patents on AI applications in healthcare and co-invented the first FDA approved AI-bioprognostic for kidney disease. His influence is reflected in external leadership roles, including Chair of the Taskforce on AI/Digital Health and Associate Editor of NPJ Digital Medicine. His mentorship has seen several of his mentees attain independent faculty roles, underscoring his commitment to fostering future leaders in medicine. He has received several honors including the ANIO rising star award, the Carl Nacht Memorial lecture and the Harold Lamport clinical research award.
Dr. Joshua Lampert, MD
Joshua M Lampert, MD, FACC is a cardiac electrophysiologist, Assistant Professor of Medicine and the Medical Director of Machine Learning for Mount Sinai Fuster Heart Hospital.
Dr. Lampert is full-time faculty at Mount Sinai Hospital where he specializes in the management of patients with heart rhythm disorders. He was a recipient of the Mount Sinai Physician of the Year award in 2021 and has been recognized on multiple occasions for delivering exceptional patient care by the Patient Comments Committee. He focuses on the treatment of patients with the full spectrum of cardiac arrhythmias including catheter-based treatment and ablation of atrial fibrillation, complex atrial flutters, supraventricular tachycardia, and ventricular arrhythmias. He performs device implants such as left atrial appendage closure devices, pacemakers, defibrillators, and novel leadless pacemaker systems. He completed his medical training in internal medicine at Columbia University Medical Center (New York Presbyterian) and his training in cardiovascular disease and clinical cardiac electrophysiology at Mount Sinai Hospital. He is board certified in internal medicine, cardiovascular disease, echocardiography, and clinical cardiac electrophysiology.
As Medical Director of Machine Learning, he develops and applies novel machine learning tools to improve patient care by augmenting the capacity to diagnose, risk stratify, and treat a variety of conditions. His work includes an ECG-based deep learning algorithm to predict which patients with premature ventricular contractions (PVCs) go on to develop weak hearts. Additionally, he studies large language models and machine learning approaches to revolutionize modern clinical decision-making. His work also traverses the intersection of novel algorithms, health system structure, and workflows to translate these innovations into clinical practice in an era of augmented intelligence. He has been recognized for his academic contributions by leading medical organizations including the 2024 Simon Dack Award from the American College of Cardiology and the 2025 William J. Mandel Most Innovative Abstract Award by the Heart Rhythm Society.
Dr. Akhil Vaid, MBBS
Dr. Akhil Vaid, MD is an Assistant Professor in the Division of Data-Driven and Digital Medicine and the Windreich Department of Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai. His research focuses on the application of machine learning and artificial intelligence in healthcare, particularly in cardiology.
Dr. Vaid has made significant contributions to the field, with numerous publications exploring deep learning techniques for analyzing medical data. His work includes developing AI models for detecting cardiac dysfunction from echocardiograms and electrocardiograms, as well as applying deep learning to natural language processing (NLP) in clinical documentation, computer vision for medical imaging analysis, and tabular data modeling for predictive analytics in healthcare. He is also deeply involved in model implementation, ensuring that AI solutions transition from research into practical, real-world clinical applications. His research is widely cited, highlighting its impact on medical AI and clinical decision-making.
Beyond research, Dr. Vaid is actively involved in teaching and mentoring, shaping the future of digital medicine. As a member of the A.I.M.S. Lab, he collaborates with a diverse team to advance AI-driven innovations in medicine and science.
About HeartSciences
HeartSciences is a medical technology company focused on applying innovative AI-based technology to an ECG (also known as an EKG) to expand and improve an ECG's clinical utility. Millions of ECGs are performed every week and the Company's objective is to improve healthcare by making it a far more valuable cardiac screening tool, particularly in frontline or point-of-care clinical settings. HeartSciences has one of the largest libraries of AI-ECG algorithms and intends to provide these AI-ECG algorithms on a device agnostic cloud-based solution as well as a low-cost ECG hardware platform. Working with clinical experts, HeartSciences ensures that all solutions are designed to work within existing clinical care pathways, making it easier for clinicians to use AI-ECG technology to improve their patient's care and lead to better outcomes. HeartSciences' first product candidate for FDA clearance, the MyoVista® wavECG™, or the MyoVista®, is a resting 12-lead ECG that is also designed to provide diagnostic information related to cardiac dysfunction which has traditionally only been available through the use of cardiac imaging. The MyoVista® also provides conventional ECG information in the same test.
For more information, please visit: https://www.heartsciences.com. X: @HeartSciences
Safe Harbor Statement
This announcement contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These forward-looking statements are made under the "safe harbor" provisions of the Private Securities Litigation Reform Act of 1995 and are relating to the Company's future financial and operating performance. All statements, other than statements of historical facts, included herein are "forward-looking statements" including, among other things, statements about HeartSciences' beliefs and expectations. These statements are based on current expectations, assumptions and uncertainties involving judgments about, among other things, future economic, competitive and market conditions and future business decisions, all of which are difficult or impossible to predict accurately and many of which are beyond the Company's control. The expectations reflected in these forward-looking statements involve significant assumptions, risks and uncertainties, and these expectations may prove to be incorrect. Investors should not place undue reliance on these forward-looking statements, which speak only as of the date of this press release. Potential risks and uncertainties include, but are not limited to, risks discussed in HeartSciences' Annual Report on Form 10-K for the fiscal year ended April 30, 2024, filed with the U.S. Securities and Exchange Commission (the "SEC") on July 29, 2024, HeartSciences' Quarterly Report on Form 10-Q for the fiscal quarter ended July 31, 2024, filed with the SEC on September 12, 2024, HeartSciences' Quarterly Report on Form 10-Q for the fiscal quarter ended October 31, 2024, filed with the SEC on December 16, 2024, HeartSciences' Quarterly Report on Form 10-Q for the fiscal quarter ended January 31, 2025, filed with the SEC on March 13, 2024 and in HeartSciences' other filings with the SEC at www.sec.gov. Other than as required under the securities laws, the Company does not assume a duty to update these forward-looking statements.
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