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Skip search results from other journals and go to results- 3 Journal of Medical Internet Research
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Based on the selected radiomics features, a radiomics model was constructed by using the support vector machine classifier. As a supervised learning method that was very effective in linear or nonlinear classification tasks, the support vector machine classifier has been widely used in radiomics analysis.
J Med Internet Res 2024;26:e56851
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Initial models were constructed using 3 distinct types of data: clinical data, CT images, and radiomics from the enrolled patient cohort. These data types were then aggregated in 2 specific combinations to generate models based on mixed input data, specifically, clinical-CT and clinical-radiomics features. Furthermore, a composite model using clinical data, CT images, and histological imaging was also developed.
J Med Internet Res 2024;26:e54944
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Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis
Radiogenomics is an emerging technology that combines radiomics and genomics, with the ultimate goal of improving prognosis and outcomes [1]. Radiogenomics can be used to investigate the relationship between imaging features and gene mutations and expression patterns [2-4].
Interact J Med Res 2024;13:e51347
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At least 1 study [13] has reported using radiomics to identify painful metastatic lesions in radiographic images. However, we found no reports in the literature of a scalable approach that can be used efficiently on a large set of unlabeled patient data. To the best of our knowledge, our work is the first to combine natural language processing (NLP) and radiomics to enable an efficient and scalable pain identification pipeline using unstructured data.
JMIR AI 2023;2:e44779
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Reference 4: Radiomics: the facts and the challenges of image analysis Reference 5: Radiomics in prostate cancer: basic concepts and current state-of-the-art Reference 57: Multiparametric MRI-Based Radiomics for Prostate Cancer Screening With PSA in 4-10 ng/mL Reference 59: Radiomics analysis potentially reduces over-diagnosis of prostate cancer with PSA levels Reference 75: Bringing radiomics into a multi-omics framework for a comprehensive genotype-phenotyperadiomics
J Med Internet Res 2021;23(4):e22394
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Radiomics can be intuitively regarded as an approach that can quantify the conversion of visual image information into deep features [16,17]. This radiomics model is based on a machine-learning approach that can help doctors make the most accurate diagnosis by mining and analyzing radiological features.
JMIR Med Inform 2020;8(10):e23578
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