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 …

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …

Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …

Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish
non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials …

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases,
such as skin, breast, and lung cancer. AI is an advanced form of technology that uses …

The World Health Organization (WHO), in their 2022 report, identified cancer as one of the
leading causes of death, accounting for about 16% of deaths worldwide. The Cancer …

Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …

Objectives To evaluate radiomics studies according to radiomics quality score (RQS) and
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or …

This paper demonstrates a computer-aided diagnosis (CAD) system for lung cancer
classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science …