Towards equitable AI in oncology
VS Viswanathan, V Parmar… - Nature Reviews Clinical …, 2024 - nature.com
Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with
considerable potential to improve early cancer detection and risk assessment, and to enable …
considerable potential to improve early cancer detection and risk assessment, and to enable …
The stability of oncologic MRI radiomic features and the potential role of deep learning: A review
The use of MRI radiomic models for the diagnosis, prognosis and treatment response
prediction of tumors has been increasingly reported in literature. However, its widespread …
prediction of tumors has been increasingly reported in literature. However, its widespread …
Multicenter evaluation of MRI‐based radiomic features: A phantom study
Introduction This work describes the development of a novel radiomics phantom designed
for magnetic resonance imaging (MRI) that can be used in a multicenter setting. The …
for magnetic resonance imaging (MRI) that can be used in a multicenter setting. The …
Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility
NW Schurink, SR van Kranen, S Roberti… - European …, 2022 - Springer
Objectives To investigate sources of variation in a multicenter rectal cancer MRI dataset
focusing on hardware and image acquisition, segmentation methodology, and radiomics …
focusing on hardware and image acquisition, segmentation methodology, and radiomics …
Reliability of MRI radiomics features in MR‐guided radiotherapy for prostate cancer: Repeatability, reproducibility, and within‐subject agreement
Purpose The MR‐guided radiotherapy (MRgRT) images on the integrated MRI and linear
accelerator (MR‐LINAC) might facilitate radiomics analysis for longitudinal treatment …
accelerator (MR‐LINAC) might facilitate radiomics analysis for longitudinal treatment …
A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer
We developed and validated a multimodal radiomic machine learning approach to
noninvasively predict the expression of lymphocyte cell-specific protein-tyrosine kinase …
noninvasively predict the expression of lymphocyte cell-specific protein-tyrosine kinase …
Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer
NW Schurink, SR van Kranen, JJM van Griethuysen… - European …, 2023 - Springer
Objectives To develop and validate a multiparametric model to predict neoadjuvant
treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI …
treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI …
[HTML][HTML] Pre-trial quality assurance of diffusion-weighted MRI for radiomic analysis and the role of harmonisation
Purpose The aim of this study was to perform a quantitative quality assurance of diffusion-
weighted MRI to assess the variability of the mean apparent diffusion coefficient (ADC) and …
weighted MRI to assess the variability of the mean apparent diffusion coefficient (ADC) and …
Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer
Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000
deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments …
deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments …
Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal cancer
Purpose: Radiomics of magnetic resonance images (MRIs) in rectal cancer can non-
invasively characterize tumor heterogeneity with potential to discover new imaging …
invasively characterize tumor heterogeneity with potential to discover new imaging …