Machine learning models for differential diagnosis of Cushing’s disease and ectopic ACTH secretion syndrome
Author:
Funder
National High Level Hospital Clinical Research Funding
National College Students Innovation and Entrepreneurship Training Program
Publisher
Springer Science and Business Media LLC
Subject
Endocrinology,Endocrinology, Diabetes and Metabolism
Link
https://link.springer.com/content/pdf/10.1007/s12020-023-03341-7.pdf
Reference28 articles.
1. M. Fleseriu, R. Auchus, I. Bancos et al. Consensus on diagnosis and management of Cushing’s disease: a guideline update. Lancet Diabetes Endocrinol. 9(12), 847–875 (2021). https://doi.org/10.1016/s2213-8587(21)00235-7
2. L.K. Nieman, Molecular derangements and the diagnosis of ACTH-dependent Cushing’s syndrome. Endocr. Rev. (2021). https://doi.org/10.1210/endrev/bnab046
3. C. Frete, J.B. Corcuff, E. Kuhn et al. Non-invasive diagnostic strategy in ACTH-dependent Cushing’s syndrome. J. Clin. Endocrinol. Metab. 105(10) (2020). https://doi.org/10.1210/clinem/dgaa409
4. K. Ritzel, F. Beuschlein, C. Berr et al. ACTH after 15 min distinguishes between Cushing’s disease and ectopic Cushing’s syndrome: a proposal for a short and simple CRH test. Eur. J. Endocrinol. 173(2), 197–204 (2015). https://doi.org/10.1530/eje-14-0912
5. E.R. Laws, M.P. Catalino, Editorial. Machine learning and artificial intelligence applied to the diagnosis and management of Cushing disease. Neurosurg. Focus 48(6), E6 (2020). https://doi.org/10.3171/2020.3.focus20213
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