Artificial intelligence in endocrinology: a comprehensive review

Background and aim Artificial intelligence (AI) has emerged as a promising technology in the field of endocrinology, offering significant potential to revolutionize the diagnosis, treatment, and management of endocrine disorders. This comprehensive review aims to provide a concise overview of the cu...

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Bibliographic Details
Published in:Journal of endocrinological investigation Vol. 47; no. 5; pp. 1067 - 1082
Main Authors: Giorgini, F., Di Dalmazi, G., Diciotti, S.
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.05.2024
Springer Nature B.V
Subjects:
Adrenal Gland Neoplasms
Algorithms
Artificial Intelligence
Bone tumors
Brain
Clinical outcomes
Datasets
Deep learning
Diabetes
Diabetes mellitus
Diagnosis
Disease
Endocrine disorders
Endocrinology
Humans
Internal Medicine
Machine Learning
Medical personnel
Medical research
Medical Subject Headings-MeSH
Medicine
Medicine & Public Health
Metabolic Diseases
Metabolism
Metabolites
Neural networks
Precision medicine
Review
Thyroid diseases
Thyroid gland
Risk prediction
Bone and mineral disorders
Pre-emptive medicine
Diabetes disorders
Machine learning
Adrenal tumors
ISSN:1720-8386, 0391-4097, 1720-8386
Online Access:Get full text
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Summary:Background and aim Artificial intelligence (AI) has emerged as a promising technology in the field of endocrinology, offering significant potential to revolutionize the diagnosis, treatment, and management of endocrine disorders. This comprehensive review aims to provide a concise overview of the current landscape of AI applications in endocrinology and metabolism, focusing on the fundamental concepts of AI, including machine learning algorithms and deep learning models. Methods The review explores various areas of endocrinology where AI has demonstrated its value, encompassing screening and diagnosis, risk prediction, translational research, and “pre-emptive medicine”. Within each domain, relevant studies are discussed, offering insights into the methodology and main findings of AI in the treatment of different pathologies, such as diabetes mellitus and related disorders, thyroid disorders, adrenal tumors, and bone and mineral disorders. Results Collectively, these studies show the valuable contributions of AI in optimizing healthcare outcomes and unveiling new understandings of the intricate mechanisms underlying endocrine disorders. Furthermore, AI-driven approaches facilitate the development of precision medicine strategies, enabling tailored interventions for patients based on their individual characteristics and needs. Conclusions By embracing AI in endocrinology, a future can be envisioned where medical professionals and AI systems synergistically collaborate, ultimately enhancing the lives of individuals affected by endocrine disorders.
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ISSN:1720-8386
0391-4097
1720-8386
DOI:10.1007/s40618-023-02235-9