Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis

A Zwanenburg - European journal of nuclear medicine and molecular …, 2019 - Springer
Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …

Emerging applications of artificial intelligence in neuro-oncology

JD Rudie, AM Rauschecker, RN Bryan, C Davatzikos… - Radiology, 2019 - pubs.rsna.org
Due to the exponential growth of computational algorithms, artificial intelligence (AI)
methods are poised to improve the precision of diagnostic and therapeutic methods in …

The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification

U Baid, S Ghodasara, S Mohan, M Bilello… - arXiv preprint arXiv …, 2021 - arxiv.org
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the
Radiological Society of North America (RSNA), the American Society of Neuroradiology …

[HTML][HTML] Federated learning enables big data for rare cancer boundary detection

S Pati, U Baid, B Edwards, M Sheller, SH Wang… - Nature …, 2022 - nature.com
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but …

Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI

NQK Le, TNK Hung, DT Do, LHT Lam, LH Dang… - Computers in Biology …, 2021 - Elsevier
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 …

[HTML][HTML] The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: Advanced MRI, clinical, genomics, & radiomics

S Bakas, C Sako, H Akbari, M Bilello, A Sotiras… - Scientific data, 2022 - nature.com
Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

Impact of image preprocessing methods on reproducibility of radiomic features in multimodal magnetic resonance imaging in glioblastoma

H Moradmand, SMR Aghamiri… - Journal of applied …, 2020 - Wiley Online Library
To investigate the effect of image preprocessing, in respect to intensity inhomogeneity
correction and noise filtering, on the robustness and reproducibility of the radiomics features …

Blueprint for cancer research: Critical gaps and opportunities

LW Elmore, SF Greer, EC Daniels… - CA: A Cancer …, 2021 - Wiley Online Library
We are experiencing a revolution in cancer. Advances in screening, targeted and immune
therapies, big data, computational methodologies, and significant new knowledge of cancer …

[PDF][PDF] Epidermal growth factor receptor extracellular domain mutations in glioblastoma present opportunities for clinical imaging and therapeutic development

ZA Binder, AH Thorne, S Bakas, EP Wileyto, M Bilello… - Cancer cell, 2018 - cell.com
We explored the clinical and pathological impact of epidermal growth factor receptor (EGFR)
extracellular domain missense mutations. Retrospective assessment of 260 de novo …

The role of epigenetics in placental development and the etiology of preeclampsia

C Apicella, CSM Ruano, C Méhats, F Miralles… - International journal of …, 2019 - mdpi.com
In this review, we comprehensively present the function of epigenetic regulations in normal
placental development as well as in a prominent disease of placental origin, preeclampsia …