[HTML][HTML] Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review
Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …
reliability are also raised. This review attempts to update and overview the current status of …
Artificial intelligence-driven assessment of radiological images for COVID-19
Y Bouchareb, PM Khaniabadi, F Al Kindi… - Computers in biology …, 2021 - Elsevier
Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …
COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients …
Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI
Background In the field of glioma, transcriptome subtypes have been considered as an
important diagnostic and prognostic biomarker that may help improve the treatment efficacy …
important diagnostic and prognostic biomarker that may help improve the treatment efficacy …
[HTML][HTML] Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature
Objective The aim of this study was to identify the most important features and assess their
discriminative power in the classification of the subtypes of NSCLC. Methods This study …
discriminative power in the classification of the subtypes of NSCLC. Methods This study …
[HTML][HTML] Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients
Purpose The aim of this study was to develop radiomics–based machine learning models
based on extracted radiomic features and clinical information to predict the risk of death …
based on extracted radiomic features and clinical information to predict the risk of death …
Multi-level multi-modality (PET and CT) fusion radiomics: prognostic modeling for non-small cell lung carcinoma
We developed multi-modality radiomic models by integrating information extracted from 18 F-
FDG PET and CT images using feature-and image-level fusions, toward improved prognosis …
FDG PET and CT images using feature-and image-level fusions, toward improved prognosis …
Treatment response prediction using MRI‐based pre‐, post‐, and delta‐radiomic features and machine learning algorithms in colorectal cancer
S Shayesteh, M Nazari, A Salahshour… - Medical …, 2021 - Wiley Online Library
Objectives We evaluate the feasibility of treatment response prediction using MRI‐based pre‐
, post‐, and delta‐radiomic features for locally advanced rectal cancer (LARC) patients …
, post‐, and delta‐radiomic features for locally advanced rectal cancer (LARC) patients …
Impact of preprocessing and harmonization methods on the removal of scanner effects in brain MRI radiomic features
Simple Summary As a rapid-development research field, radiomics-based analysis has
been applied to many clinical problems. However, the reproducibility of the radiomics …
been applied to many clinical problems. However, the reproducibility of the radiomics …
Fetal MRI radiomics: non-invasive and reproducible quantification of human lung maturity
F Prayer, ML Watzenböck, BH Heidinger, J Rainer… - European …, 2023 - Springer
Objectives To assess the reproducibility of radiomics features extracted from the developing
lung in repeated in-vivo fetal MRI acquisitions. Methods In-vivo MRI (1.5 Tesla) scans of 30 …
lung in repeated in-vivo fetal MRI acquisitions. Methods In-vivo MRI (1.5 Tesla) scans of 30 …
Endorectal ultrasound radiomics in locally advanced rectal cancer patients: despeckling and radiotherapy response prediction using machine learning
Purpose The current study aimed to evaluate the association of endorectal ultrasound (EUS)
radiomics features at different denoising filters based on machine learning algorithms and to …
radiomics features at different denoising filters based on machine learning algorithms and to …