Data-driven analysis of influence between radiologists for diagnosis of breast lesions

DOI10.1007/s10479-022-05086-4OpenAlexW4311622262MaRDI QIDQ6179180

Dongyue Wang, Chao Fu, Wen-Jun Chang

Publication date: 5 September 2023

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-022-05086-4

zbMATH Keywords

influence analysisstatistical comparisondiagnosis of breast lesionmachine learning regression algorithmorganizational development

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Artificial intelligence (68Txx) Operations research and management science (90Bxx)

Cites Work

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• Simple and absolute special majorities generated by OWA operators
• Robust regression: Asymptotics, conjectures and Monte Carlo
• Cost-sensitive business failure prediction when misclassification costs are uncertain: a heterogeneous ensemble selection approach
• Data-driven multiple criteria decision making for diagnosis of thyroid cancer
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Random forests
• Stochastic gradient boosting.
• An ensemble method of the machine learning to prognosticate the gastric cancer

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