External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
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 …
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
International evaluation of an AI system for breast cancer screening
Screening mammography aims to identify breast cancer at earlier stages of the disease,
when treatment can be more successful. Despite the existence of screening programmes …
when treatment can be more successful. Despite the existence of screening programmes …
Designing deep learning studies in cancer diagnostics
A Kleppe, OJ Skrede, S De Raedt, K Liestøl… - Nature Reviews …, 2021 - nature.com
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
[HTML][HTML] A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta …
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine
F Pesapane, M Codari, F Sardanelli - European radiology experimental, 2018 - Springer
One of the most promising areas of health innovation is the application of artificial
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …
Stand-alone artificial intelligence for breast cancer detection in mammography: comparison with 101 radiologists
A Rodriguez-Ruiz, K Lång… - JNCI: Journal of the …, 2019 - academic.oup.com
Background Artificial intelligence (AI) systems performing at radiologist-like levels in the
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …
Standalone AI for breast cancer detection at screening digital mammography and digital breast tomosynthesis: a systematic review and meta-analysis
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 …
systems in mammographic screening. However, it is essential to critically evaluate the …
[HTML][HTML] Artificial intelligence in retina
U Schmidt-Erfurth, A Sadeghipour, BS Gerendas… - Progress in retinal and …, 2018 - Elsevier
Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …
condition of the retina and beyond ocular disease. Digital images providing millions of …
Detection of breast cancer with mammography: effect of an artificial intelligence support system
Purpose To compare breast cancer detection performance of radiologists reading
mammographic examinations unaided versus supported by an artificial intelligence (AI) …
mammographic examinations unaided versus supported by an artificial intelligence (AI) …