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Un algoritmo basato sul machine learning come approccio innovativo per la diagnosi differenziale tra diabete insipido e polidipsia primaria nella pratica clinica

  • NOVITÀ IN ENDOCRINOLOGIA
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Bibliografia

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  1. Patologie Ipotalamo-Ipofisarie e Alterazioni del Sodio Unit, S.O.D. Endocrinologia, A.O.U. Careggi, Dipartimento di Scienze Biomediche Sperimentali e Cliniche “Mario Serio”, Università degli Studi di Firenze, Firenze, Italia

    Alessandro Peri

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  1. Alessandro Peri
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Correspondence to Alessandro Peri.

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Peri, A. Un algoritmo basato sul machine learning come approccio innovativo per la diagnosi differenziale tra diabete insipido e polidipsia primaria nella pratica clinica. L'Endocrinologo 24, 452–453 (2023). https://doi.org/10.1007/s40619-023-01337-z

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  • DOI: https://doi.org/10.1007/s40619-023-01337-z

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