Patient classification and attribute assessment based on machine learning techniques in the qualification process for surgical treatment of adrenal tumours

• Published in: Scientific reports Vol. 14; no. 1; p. 11209
• Main Authors: Wielogórska-Partyka, Marta, Adamski, Marcin, Siewko, Katarzyna, Popławska-Kita, Anna, Buczyńska, Angelika, Myśliwiec, Piotr, Krętowski, Adam Jacek, Adamska, Agnieszka
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 16.05.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705; 692/163; Accuracy; Adrenal Gland Neoplasms - diagnostic imaging; Adrenal Gland Neoplasms - pathology; Adrenal Gland Neoplasms - surgery; Adrenal glands; Adrenalectomy; Adrenalectomy - methods; Adult; Aged; Algorithms; Classification; Computed tomography; Female; Humanities and Social Sciences; Humans; Learning algorithms; Machine Learning; Male; Middle Aged; multidisciplinary; Patients; Science; Science (multidisciplinary); Statistical analysis; Tomography, X-Ray Computed

Adrenal gland incidentaloma is frequently identified through computed tomography and poses a common clinical challenge. Only selected cases require surgical intervention. The primary aim of this study was to compare the effectiveness of selected machine learning (ML) techniques in proper qualifying...