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A Glimpse into the Realm that Combines Artificial Intelligence and Endocrinology
Minal Pande1, Shinjan Patra2, Soubhik Rudra3
1Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, Nagpur, Maharashtra, India.
Indian Journal of Endocrinology and Metabolism
|November 13, 2025
Summary
Artificial Intelligence (AI) enhances healthcare by improving data assimilation and patient care. In endocrinology, AI aids in diagnostics, disease management, and predicting complications, showcasing its growing clinical utility.
Area of Science:
- Endocrinology and Metabolism
- Medical Informatics
- Artificial Intelligence in Healthcare
Background:
- The healthcare sector is rapidly integrating Artificial Intelligence (AI) to manage vast datasets and improve patient outcomes cost-effectively.
- AI is increasingly utilized in endocrinology for screening, diagnostics, and disease management, addressing complex metabolic and endocrine disorders.
Purpose of the Study:
- To provide a concise overview of current Artificial Intelligence applications within the field of endocrinology and metabolism.
- To highlight the role of machine learning algorithms and deep-learning models in advancing endocrine care.
Main Methods:
- Review of existing literature on AI applications in endocrinology.
- Focus on key AI concepts like machine learning and deep learning.
Main Results:
- AI demonstrates significant utility in diagnosing thyroid nodules and detecting adrenal malignancies.
- AI assists in predicting diabetes microvascular complications, estimating osteoporosis risk, and calculating bone age.
- Applications include closed-loop insulin delivery algorithms and predicting survival in endocrine cancers.
Conclusions:
- AI is a powerful tool revolutionizing endocrinology and metabolism through enhanced diagnostics and patient management.
- The integration of AI, particularly machine learning and deep learning, promises further advancements in endocrine care and research.
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