This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evolving field of artificial intelligence (AI). The range of AI applications is broad. AI can be used for breast cancer risk estimation that could allow f...
BACKGROUND: Lung cancer is the principal cause of cancer-related deaths worldwide. Early detection of lung cancer with screening is indispensable to reduce the high morbidity and mortality rates. Artificial intelligence (AI) is widely utilised in hea...
Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed...
Clinics and research in hepatology and gastroenterology
Dec 7, 2022
The current "Gold Standard" colorectal cancer (CRC) screening approach of faecal occult blood test (FOBT) with follow-up colonoscopy has been shown to significantly improve morbidity and mortality, by enabling the early detection of disease. However,...
IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest...
Artificial intelligence (AI) has been a very active research topic over the last years and thoracic imaging has particularly benefited from the development of AI and in particular deep learning. We have now entered a phase of adopting AI into clinica...
Proceedings of the National Academy of Sciences of the United States of America
Nov 7, 2022
Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of the T cells to penetrate the tumor stroma, thereby significantly lim...
Journal of applied clinical medical physics
Oct 9, 2022
OBJECTIVES: To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low-dose chest CT in comparison with 40% adaptive statistical iterative reconstruction-Veo (ASiR-V40%) algorithm.