Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …

Artificial intelligence (AI) is a new technical discipline that uses computer technology to
research and develop the theory, method, technique, and application system for the …

Care during the COVID-19 pandemic hinges upon the existence of fast, safe, and highly
sensitive diagnostic tools. Considering significant practical advantages of lung ultrasound …

To recognize the epidermal growth factor receptor (EGFR) gene mutation status in lung
adenocarcinoma (LADC) has become a prerequisite of deciding whether EGFR-tyrosine …

Ultrasound (US) imaging holds promise as a low-cost versatile, non-invasive point-of-care
diagnostic modality in low-and middle-income countries (LMICs). Still, lung US can be …

Machine learning (ML) methods are pervading an increasing number of fields of application
because of their capacity to effectively solve a wide variety of challenging problems. The …

Evaluating the trustworthiness of deep learning-based computer-aided diagnosis (CAD)
systems is challenging. There is a need to optimize trust and performance in model …

Lung cancer is a prevalent malignancy that impacts individuals of all genders and is often
diagnosed late due to delayed symptoms. To catch it early, researchers are developing …

Breast cancer (BrCa) is the most common disease in women worldwide. Classifying the
BrCa image is extremely important for finding BrCa at an earlier stage and monitoring BrCa …

AIM To develop and validate a nomogram model that combines computed tomography (CT)-
based radiological factors extracted from deep-learning and clinical factors for the early …