Machine Learning May Be an Alternative to BIPSS in the Differential Diagnosis of ACTH-dependent Cushing Syndrome

Sadeleştirilmiş öğe sayfası
dc.contributor.authorDemir, Ahmet Numan
dc.contributor.authorAyata, Deger
dc.contributor.authorOz, Ahmet
dc.contributor.authorSulu, Cem
dc.contributor.authorKara, Zehra
dc.contributor.authorSahin, Serdar
dc.contributor.authorOzaydin, Dilan
dc.contributor.authorKorkmazer, Bora
dc.contributor.authorArslan, Serdar
dc.contributor.authorKizilkilic, Osman
dc.contributor.authorCiftci, Sema
dc.contributor.authorCelik, Ozlem
dc.contributor.authorOzkaya, Hande Mefkure
dc.contributor.authorTanriover, Necmettin
dc.contributor.authorGazioglu, Nurperi
dc.contributor.authorKadioglu, Pinar
dc.date.accessioned2025-10-16T15:13:37Z
dc.date.issued2024
dc.identifier.doi10.1210/clinem/dgae180
dc.identifier.otherWOS:001199553700001
dc.identifier.urihttps://openaccess.acibadem.edu.tr/handle/11443/5885
dc.publisherENDOCRINE SOC
dc.sourceJOURNAL OF CLINICAL ENDOCRINOLOGY \& METABOLISM
dc.subjectbilateral inferior petrosal sinus sampling
dc.subjectCushing disease
dc.subjectCushing syndrome
dc.subjectectopic ACTH syndrome
dc.subjectmachine learning
dc.titleMachine Learning May Be an Alternative to BIPSS in the Differential Diagnosis of ACTH-dependent Cushing Syndrome
dc.typeArticle

Dosyalar

Koleksiyonlar

WOS