Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

The purpose of this article is to review options for more rapid diagnosis of lung cancer at an
earlier stage, thereby improving survival. These options include screening, allowing general …

Background Immune checkpoint blockade (ICB) induces durable immune responses across
a spectrum of advanced cancers and revolutionizes the oncology field. However, only a …

Lung cancer remains a prevalent and deadly disease, claiming numerous lives annually.
Early detection plays a pivotal role in significantly improving survival rates, by up to 50–70 …

Background Risk prediction models of lung nodules have been built to alleviate the heavy
interpretative burden on clinicians. However, the malignancy scores output by those models …

Challenges drive the state-of-the-art of automated medical image analysis. The quantity of
public training data that they provide can limit the performance of their solutions. Public …

Content-based medical image retrieval (CBMIR) systems can assist and help doctors and
radiologists in reliable diagnosis by retrieving relevant medical cases from past cases that …

Radiomics, analysing quantitative features from medical imaging, has rapidly become an
emerging field in translational oncology. Radiomics has been investigated in several …

In 2015, around 4400 individuals received a diagnosis of lung cancer, and Switzerland
recorded approximately 3200 deaths related to lung cancer. Advances in detection, such as …

In recent times, current healthcare imaging investigation, both for analytical and treatment
reasons involves Artificial Intelligence (AI). AI has been used by research scientists to …