BACKGROUND: Early detection of cancer can help patients with more effective treatments and result in better prognosis. Unfortunately, established cancer screening technologies are limited for use, especially for multi-cancer early detection. In this ...
BACKGROUND: This scoping review systematically maps externally validated machine learning (ML)-based models in cancer patient care, quantifying their performance, and clinical utility, and examining relationships between models, cancer types, and cli...
Cancer biotherapy & radiopharmaceuticals
Feb 20, 2025
Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging specialists in radiology and nuclear medicine, where radiomics can consistently outperform human analysis and reporting capability, and do it faster, with ...
PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer include severe side effects (such as potentially life threatening pneumonitis [PN]), which can cause the discontinuation of treatment. Predicting which p...
Mathematical modelling has proven to be a valuable tool in predicting the delivery and efficacy of molecular, antibody-based, nano and cellular therapy in solid tumours. Mathematical models based on our understanding of the biological processes at su...
PURPOSE OF REVIEW: This review explores the role of artificial intelligence (AI) in cardio-oncology, focusing on its latest application across problems in diagnosis, prognosis, risk stratification, and management of cardiovascular (CV) complications ...
Journal of applied clinical medical physics
Feb 17, 2025
Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredicta...
BACKGROUND: The ability of machine learning (ML) to process and learn from large quantities of heterogeneous patient data is gaining attention in the precision oncology community. Some remarkable developments have taken place in the domain of image c...
Cell classification based on histopathology images is crucial for tumor recognition and cancer diagnosis. Using deep learning, classification accuracy is hugely improved. Semi-supervised learning is an advanced deep learning approach that uses both l...
International journal of medical informatics
Feb 13, 2025
OBJECTIVES: While prior machine learning (ML) models for cancer survivability prediction often treated all cancer stages uniformly, cancer survivability prediction should involve understanding how different stages impact the outcomes. Additionally, t...