Summary of the OCCC values for 150 radiomics features.
收藏NIAID Data Ecosystem2026-03-10 收录
数据链接：
官方服务：
资源简介：
Summary of the OCCC values for 150 radiomics features.
应用场景：
创建时间：
2017-12-14
相关数据集
DataSheet_1_The Role of Preoperative Computed Tomography Radiomics in Distinguishing Benign and Malignant Tumors of the Parotid Gland.docx
ObjectiveThis study aimed to develop and validate an integrated prediction model based on clinicoradiological data and computed tomography (CT)-radiomics for differentiating between benign and maligna
NIAID Data Ecosystem60
DataSheet_1_Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient’s Pathological Grades.docx
PurposeTo evaluate the value of multiple machine learning methods in classifying pathological grades (G1,G2, and G3), and to provide the best machine learning method for the identification of patholog
NIAID Data Ecosystem30
Validity and reproducibility of retinal arteriole and venule diameter measurements: ELSA-Brasil study. A cross-sectional study
ABSTRACT BACKGROUND: Investigation of alterations to retinal microvasculature may contribute towards understanding the role of such changes in the pathophysiology of several chronic non-communicable d
Figshare2018-08-01 更新10
SUPPLEMENTARY MATERIAL.docx
A concise statement of the major contents The study developed and validated a nomogram combining BMUS radiomics and the ACR TI-RADS. The predictive performance and stability of the nomogram was asse
NIAID Data Ecosystem30
Data_Sheet_1_Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma.docx
The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to
NIAID Data Ecosystem20
