Call for papers "Artificial intelligence in cardiovascular endocrinology: advancing precision in cardiometabolic care"

In response to the rapid developments in this space, we invite clinicians, researchers, and healthcare innovators to contribute to this emerging field through original research, reviews, perspectives, and clinical case studies.
Call for papers "Artificial intelligence in cardiovascular endocrinology: advancing precision in cardiometabolic care"
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In recent years, artificial intelligence (AI) has begun to permeate the clinical landscape—not as a distant promise, but as a transformative force in real-time decision-making. Nowhere is this transformation more compelling than at the crossroads of cardiovascular endocrinology, where hormonal disorders and metabolic dysregulation drive some of the world’s most pressing cardiovascular challenges.

Endocrine disorders such as diabetes, thyroid dysfunction, and adrenal abnormalities are major contributors to cardiovascular morbidity and mortality. Yet the tools traditionally used to assess cardiovascular risk often fail to capture the nuanced and dynamic nature of these diseases. AI is poised to fill this gap.

Emerging machine learning models can now detect early cardiovascular complications in patients with metabolic disorders, identify risk trajectories that are invisible to conventional clinical tools, and integrate vast amounts of data—from electronic health records and laboratory results to imaging and genomics—into clinically meaningful insights. Moreover, AI-powered wearable technologies are facilitating continuous, real-time monitoring, offering clinicians unprecedented opportunities for early intervention and personalized care outside traditional healthcare settings.

Despite these advances, key challenges remain. Algorithmic bias, lack of transparency in AI decision-making, and disparities in access to digital technologies are serious concerns that demand thoughtful and interdisciplinary solutions. Clinicians and researchers must be actively involved in shaping how AI is developed, validated, and implemented to ensure its safe and equitable use across diverse patient populations.

We welcome submissions addressing, but not limited to:

  • AI-based prediction and prevention of cardiovascular events in endocrine disorders
  • Integration of AI with imaging, laboratory, and wearable data in clinical practice
  • Development of clinical decision support systems for cardiometabolic management
  • Applications of AI in diabetic cardiomyopathy and other endocrine-related heart diseases
  • Ethical, legal, and health equity considerations in the deployment of AI technologies

This is a pivotal moment for the evolution of precision medicine in cardiometabolic care. By harnessing the power of AI, we have the opportunity to redefine standards of care, close diagnostic gaps, and improve outcomes for high-risk patient populations.

We encourage you to submit your work and join us in advancing this important and timely field. Together, let us shape a future where intelligent systems complement clinical expertise for the benefit of all.

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Endocrinology
Life Sciences > Health Sciences > Clinical Medicine > Endocrinology
Artificial Intelligence
Mathematics and Computing > Computer Science > Artificial Intelligence

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