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Endocrine Abstracts (2021) 73 S18.1 | DOI: 10.1530/endoabs.73.S18.1

Hospital Germans Trias Pujol, Department of Endocrinology, Badalona, Spain


There are different activities related to health care that are currently generating a large amount of data. Real-world evidence studies are becoming an important source of information that complements the one produced through other sources of evidence. On top of this, current knowledge in the field of massive data analysis allows processing of these data to produce relevant information that will eventually help clinicians in many aspects of their daily practice, especially regarding decision making. The aim of this talk is to provide the non-expert view on the applicability of the information produced from big data and its innovative analytical methodology. Several examples on the applicability of this approach in the field of endocrine and metabolic diseases will be provided during this presentation: endocrine imaging, thyroid disease, diabetes mellitus, obesity, and other endocrine conditions. Examples will include the application of AI in key areas like prevention, diagnosis, monitoring, therapeutics, and prognosis. The use of information obtained from big data through newer analytical approaches (e.g., artificial intelligence) will the basis of a changing scenario in the clinical practice of endocrinologists in the forthcoming years. Further, improved data management and newer tools derived from more precise information will contribute a better implementation of individualized endocrinology.

Volume 73

European Congress of Endocrinology 2021

Online
22 May 2021 - 26 May 2021

European Society of Endocrinology 

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