Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …

Deep learning is gaining importance due to its wide range of applications. Many researchers
have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This …

Statistics have demonstrated that one of the main factors responsible for the high mortality
rate related to lung cancer is the late diagnosis. Precision medicine practices have shown …

Abstract Coronavirus disease (COVID-19) is a severe infectious disease that causes
respiratory illness and has had devastating medical and economic consequences globally …

Deep Learning (DL) based classification algorithms have been shown to achieve top results
in clinical diagnosis, namely with lung cancer datasets. However, the complexity and …

Objective To assist clinicians in arranging personalized treatment, planning follow‐up
programs and extending survival times for non‐small cell lung cancer (NSCLC) patients, a …

Introduction It is challenging to diagnose and manage incidentally detected pulmonary
subsolid nodules due to their indolent nature and heterogeneity. The objective of this study …

The early disease of pulmonary nodules on CT images is vital for the optimum patient
treatment. We present a CAD system for pulmonary nodule identification in this paper, which …

The idea of an intelligent machine has fascinated humans for centuries. But what is
intelligence? Some define it as the capacity for learning, reasoning, understanding or, from a …

Deep learning is the state-of-the-art for medical imaging tasks, but requires large, labeled
datasets. For risk prediction, large datasets are rare since they require both imaging and …