C

CARL J. VYBRONY

University of Chicago

Publishes on AI in cancer detection, Biomedical Text Mining and Ontologies, Radiomics and Machine Learning in Medical Imaging. 1 papers and 361 citations.

1Publications
361Total Citations

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Top publicationsby citations

Improvement in Radiologists?? Detection of Clustered Microcalcifications on Mammograms
Heang‐Ping Chan, Kunio Doi, CARL J. VYBRONY et al.|Investigative Radiology|1990
Cited by 361

Relatively simple, but important, detection tasks in radiology are nearing accessibility to computer-aided diagnostic (CAD) methods. The authors have studied one such task, the detection of clustered microcalcifications on mammograms, to determine whether CAD can improve radiologists' performance under controlled but generally realistic circumstances. The results of their receiver operating characteristic (ROC) study show that CAD, as implemented by their computer code in its present state of development, does significantly improve radiologists' accuracy in detecting clustered microcalcifications under conditions that simulate the rapid interpretation of screening mammograms. The results suggest also that a reduction in the computer's false-positive rate will further improve radiologists' diagnostic accuracy, although the improvement falls short of statistical significance in this study.