The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …

Radiomics refers to the extraction of mineable data from medical imaging and has been
applied within oncology to improve diagnosis, prognostication, and clinical decision support …

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 …

Purpose An ever-growing number of predictive models used to inform clinical decision
making have included quantitative, computer-extracted imaging biomarkers, or “radiomic …

Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …

The domain of investigation of radiomics consists of large-scale radiological image analysis
and association with biological or clinical endpoints. The purpose of the present study is to …

Purposes To evaluate the capability of PET/CT images for differentiating the histologic
subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from …

Simple Summary Brain MRI scans often require different imaging sequences based on
tissue types, posing a common challenge. In our research, we propose a method that utilizes …

The advancement of artificial intelligence concurrent with the development of medical
imaging techniques provided a unique opportunity to turn medical imaging from mostly …