Belief network for grading prostate lesions.
A Bayesian belief network for grading prostatic lesions into eight primary Gleason grades was developed and tested. The network employs 13 diagnostic clues, 8 based on tissue architectural features and 5 based on nuclear features. For every diagnostic clue, three to five different outcomes are specified by membership functions. The network works in a robust fashion and attained agreement with consensus visual grading in 241 of 256 microscopic fields.
Bibbo
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M
Department of Pathology and Cell Biology, Jefferson Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania 19107-5244.
Bartels
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PH
Pfeifer
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Thompson
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D
Minimo
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Davidson
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HG
D000230:Adenocarcinoma / Q000473:pathology* / Q000648:ultrastructure; D001499:Bayes Theorem; D002467:Cell Nucleus / Q000473:pathology; D003937:Diagnosis, Differential; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000648:ultrastructure