Artificial Intelligence (AI) has recently altered the landscape of cancer research and medical
oncology using traditional Machine Learning (ML) algorithms and cutting-edge Deep …

Abstract Machine learning is an important artificial intelligence technique that is widely
applied in cancer diagnosis and detection. More recently, with the rise of personalised and …

Introduction In the UK, most people with lung cancer are diagnosed at a late stage when
curative treatment is not possible. To aid earlier detection, the socio-demographic and early …

Background: Early prediction of symptoms and mortality risks for COVID-19 patients would
improve healthcare outcomes, allow for the appropriate distribution of healthcare resources …

Wang et al.(13) presented a method to construct a prediction model of EGFR mutation-
induced drug resistance in lung cancer by combining pathological and demographic data …

Purpose This study aimed to explore patients' experiences of palliative chemotherapy for
non-small cell lung cancer (NSCLC), how patients adapt to their new and challenging life …

Purpose The aim of the present study was to investigate the predictive ability for lung cancer
of symptoms reported in an adaptive e-questionnaire, separately for never smokers, former …

Background Lung cancer remains a significant public health concern, accounting for a
considerable number of cancer-related deaths worldwide. Neural networks have emerged …

Lack of the established noninvasive diagnostic biomarkers causes delay in diagnosis of
lung cancer (LC). The aim of this study was to explore the association between inflammatory …

We aimed to firstly determine the 1-year predictive values of lung cancer alarm symptoms in
the general population and to analyse the proportion of alarm symptoms reported prior to …