From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment

K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou - Cell, 2023 - cell.com
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Artificial intelligence and machine learning in cancer imaging

DM Koh, N Papanikolaou, U Bick, R Illing… - Communications …, 2022 - nature.com
An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

B Vasey, M Nagendran, B Campbell, DA Clifton… - bmj, 2022 - bmj.com
A growing number of artificial intelligence (AI)-based clinical decision support systems are
showing promising performance in preclinical, in silico, evaluation, but few have yet …

Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis

R Aggarwal, V Sounderajah, G Martin, DSW Ting… - NPJ digital …, 2021 - nature.com
Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review

K Loizidou, R Elia, C Pitris - Computers in Biology and Medicine, 2023 - Elsevier
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …

Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy

K Freeman, J Geppert, C Stinton, D Todkill, S Johnson… - bmj, 2021 - bmj.com
Objective To examine the accuracy of artificial intelligence (AI) for the detection of breast
cancer in mammography screening practice. Design Systematic review of test accuracy …

Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches

J Zhang, J Wu, XS Zhou, F Shi, D Shen - Seminars in Cancer Biology, 2023 - Elsevier
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …

Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis

C Leibig, M Brehmer, S Bunk, D Byng… - The Lancet Digital …, 2022 - thelancet.com
Background We propose a decision-referral approach for integrating artificial intelligence
(AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on …

Medical image analysis based on deep learning approach

M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

Standalone AI for breast cancer detection at screening digital mammography and digital breast tomosynthesis: a systematic review and meta-analysis

JH Yoon, F Strand, PAT Baltzer, EF Conant, FJ Gilbert… - Radiology, 2023 - pubs.rsna.org
Background There is considerable interest in the potential use of artificial intelligence (AI)
systems in mammographic screening. However, it is essential to critically evaluate the …