Results 31 to 40 of about 48,979 (300)
Scientific Reports, 2021 Glioblastoma is the most common primary brain tumor. Standard therapy consists of maximum safe resection combined with adjuvant radiochemotherapy followed by chemotherapy with temozolomide, however prognosis is extremely poor.
Alonso Garcia-Ruiz +9 more
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Radiomics in immuno-oncology [PDF]
Immuno-Oncology and Technology, 2021 With the ongoing advances in imaging techniques, increasing volumes of anatomical and functional data are being generated as part of the routine clinical workflow. This surge of available imaging data coincides with increasing research in quantitative imaging, particularly in the domain of imaging features. An important and novel approach is radiomics,
Bodalal, Z. +3 more
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Frontiers in Oncology, 2021 BackgroundWith the improvement of ultrasound imaging resolution and the application of various new technologies, the detection rate of thyroid nodules has increased greatly in recent years. However, there are still challenges in accurately diagnosing the
Shi Yan Guo +4 more
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International Journal of Spine Surgery, 2023 Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis.
Daniel, Alsoof +5 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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Nuclear Medicine Communications, 2022 Cancer treatment is heading towards precision medicine driven by genetic and biochemical markers. Various genetic and biochemical markers are utilized to render personalized treatment in cancer. In the last decade, noninvasive imaging biomarkers have also been developed to assist personalized decision support systems in oncology. The imaging biomarkers
Jha, Ashish Kumar +6 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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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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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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