Immunotherapy offers the potential for durable clinical benefit but calls into question the
association between tumor size and outcome that currently forms the basis for imaging …

Purpose Prediction of immunotherapy response and outcome in patients with non-small cell
lung cancer (NSCLC) is challenging due to intratumoral heterogeneity and lack of robust …

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already
assumed pandemic proportions, affecting over 100 countries in few weeks. A global …

Radiomics is a technique that extracts quantitative features from medical images using data‐
characterization algorithms. Radiomic features can be used to identify tissue characteristics …

Predictive models based on radiomics and machine-learning (ML) need large and
annotated datasets for training, often difficult to collect. We designed an operative pipeline …

Purpose To compare prediction of disease outcome, severity, and patient triage in
coronavirus disease 2019 (COVID-19) pneumonia with whole lung radiomics, radiologists' …

The evaluation of the efficacy of different therapies is of paramount importance for the
patients and the clinicians in oncology, and it is usually possible by performing imaging …

Personalized medicine has revolutionized approaches to treatment in the field of lung
cancer by enabling therapies to be specific to each patient. However, physicians encounter …

Background Checkpoint inhibition has radically improved the perspective for patients with
metastatic cancer, but predicting who will not respond with high certainty remains difficult …

Immunotherapies are leading to improved outcomes for many cancers, including those with
devastating prognoses. As therapies like immune checkpoint inhibitors (ICI) become a …