Results 31 to 40 of about 42,977 (292)
Nature Reviews Clinical Oncology, 2017 Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research.
Muhammad Idris +2 more
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Diagnostics, 2023 In recent years, radiomics has been among the most impactful topics in the research field of quantitative imaging [...]
Zerunian, Marta +2 more
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Deep learning based identification of bone scintigraphies containing metastatic bone disease foci
Cancer Imaging, 2023 Purpose Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often ...
Abdalla Ibrahim +18 more
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Application of radiomics in predicting the preoperative risk stratification of gastric stromal tumors [PDF]
, 2022 PURPOSEThe stomach is the most common site of gastrointestinal stromal tumors (GISTs). In this study, clinical model, radiomics models, and nomogram were constructed to compare and assess the clinical value of each model in predicting the preoperative ...
Gao-Feng Shi +5 more
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Radiomics and Deep Radiomics for precision medicine
, 2021 {"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.
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A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma [PDF]
, 2018 PURPOSE:We aimed to develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).METHODS:A total of 304 eligible patients with HCC were randomly ...
Jie Zhou +5 more
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Frontiers in Oncology, 2021 ObjectiveTo build and validate an MRI-based radiomics nomogram to predict the therapeutic response to neoadjuvant chemoradiotherapy (nCRT) in rectal mucinous adenocarcinoma (RMAC).MethodsTotally, 92 individuals with pathologically confirmed RMAC ...
Zhihui Li +9 more
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Radiomics with artificial intelligence: a practical guide for beginners [PDF]
, 2019 Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high number of quantitative features from medical images. Artificial intelligence (AI) is broadly a set of advanced computational algorithms that basically learn ...
Ece Ateş +3 more
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Applications and limitations of radiomics [PDF]
Physics in Medicine and Biology, 2016 Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized ...
Stephen S F, Yip, Hugo J W L, Aerts
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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
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