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 …
The role of artificial intelligence in early cancer diagnosis
B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …
effective treatment in many tumour groups. Key approaches include screening patients who …
Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy
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 …
cancer in mammography screening practice. Design Systematic review of test accuracy …
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis
Background We propose a decision-referral approach for integrating artificial intelligence
(AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on …
(AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on …
External evaluation of 3 commercial artificial intelligence algorithms for independent assessment of screening mammograms
M Salim, E Wåhlin, K Dembrower, E Azavedo… - JAMA …, 2020 - jamanetwork.com
Importance A computer algorithm that performs at or above the level of radiologists in
mammography screening assessment could improve the effectiveness of breast cancer …
mammography screening assessment could improve the effectiveness of breast cancer …
Natural language processing for mental health interventions: a systematic review and research framework
Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …
Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach
Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref.). To
achieve earlier cancer detection, health organizations worldwide recommend screening …
achieve earlier cancer detection, health organizations worldwide recommend screening …
Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study
K Dembrower, E Wåhlin, Y Liu, M Salim… - The Lancet Digital …, 2020 - thelancet.com
Background We examined the potential change in cancer detection when using an artificial
intelligence (AI) cancer-detection software to triage certain screening examinations into a no …
intelligence (AI) cancer-detection software to triage certain screening examinations into a no …
Toward robust mammography-based models for breast cancer risk
Improved breast cancer risk models enable targeted screening strategies that achieve
earlier detection and less screening harm than existing guidelines. To bring deep learning …
earlier detection and less screening harm than existing guidelines. To bring deep learning …
Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers
E Sezgin - Digital health, 2023 - journals.sagepub.com
The utilization of artificial intelligence (AI) in clinical practice has increased and is evidently
contributing to improved diagnostic accuracy, optimized treatment planning, and improved …
contributing to improved diagnostic accuracy, optimized treatment planning, and improved …