Results 51 to 60 of about 78,684 (363)
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Nature Communications, 2014 Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features.
H. Aerts +16 more
semanticscholar +1 more source
Radiomics in medical imaging—“how-to” guide and critical reflection
Insights into Imaging, 2020 Radiomics is a quantitative approach to medical imaging, which aims at enhancing the existing data available to clinicians by means of advanced mathematical analysis.
J. V. van Timmeren +4 more
semanticscholar +1 more source
Frontiers in Oncology, 2021 PurposeWe aimed to explore potential confounders of prognostic radiomics signature predicting survival outcomes in clear cell renal cell carcinoma (ccRCC) patients and demonstrate how to control for them.Materials and MethodsPreoperative contrast ...
Lin Lu +9 more
doaj +1 more source
Future Artificial Intelligence tools and perspectives in medicine [PDF]
Curr Opin Urol. 2021 Jul 1;31(4):371-377, 2022 Purpose of review: Artificial intelligence (AI) has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis. These tools are typically employed on medical data (i.e., image, molecular data, clinical variables, etc.) and used the statistical and machine learning methods to measure the model ...
arxiv +1 more source
Radiomics applications in cardiac imaging: a comprehensive review
La radiologia medica, 2023 Radiomics is a new emerging field that includes extraction of metrics and quantification of so-called radiomic features from medical images. The growing importance of radiomics applied to oncology in improving diagnosis, cancer staging and grading, and ...
Tiziano Polidori +12 more
semanticscholar +1 more source
Frontiers in Oncology, 2021 BackgroundPostoperative cerebral edema is common in patients with meningioma. It is of great clinical significance to predict the postoperative cerebral edema exacerbation (CEE) for the development of individual treatment programs in patients with ...
Bing Xiao +10 more
doaj +1 more source
MRI radiomic features are independently associated with overall survival in soft tissue sarcoma [PDF]
, 2019 Purpose: Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR ...
Ball, Kevin C +11 more
core +2 more sources
Frontiers in Immunology, 2023 Introduction The treatment response to neoadjuvant immunochemotherapy varies among patients with potentially resectable non-small cell lung cancers (NSCLC) and may have severe immune-related adverse effects.
Chaoyuan Liu +17 more
semanticscholar +1 more source
Radiomics and Deep Radiomics for precision medicine
, 2022 {"references": ["E Bertelli, L Mercatelli, C Marzi, E Pachetti, M Baccini, et al. Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI., Fron in Oncology, 5515, 2021, https://doi.org/10.3389/fonc.2021.802964", "F Gioia, MA Pascali, A Greco, S Colantonio, EP Scilingo.
openaire +2 more sources
Frontiers in Oncology, 2023 BackgroundFor patients with gastric cancer (GC), effective preoperative identification of peritoneal metastasis (PM) remains a severe challenge in clinical practice. Regrettably, effective early identification tools are still lacking up to now.
Fan Zhang, Guoxue Wu, Nan Chen, Ruyue Li
doaj +1 more source