Neural network analysis for evaluating cancer risk in thyroid nodules with an indeterminate diagnosis at aspiration cytology: Identification of a low-risk subgroup

Thyroid

Volumn 14, Issue 12, 2004, Pages 1065-1071

  Ippolito, Antonio M ^a   De Laurentiis, Michelino ^b   La Rosa, Giacomo L ^a   Eleuteri, Antonio ^b   Tagliaferri, Roberto ^c   De Placido, Sabino ^b   Vigneri, Riccardo ^a   Belfiore, Antonino ^d,e  

^a GARIBALDI HOSPITAL   (Italy)

^b UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^c UNIVERSITY OF SALERNO   (Italy)

^d Policlinico Mater Domini   (Italy)

^e UNIVERSITY MAGNA GRAECIA OF CATANZARO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; ASPIRATION BIOPSY; ASPIRATION CYTOLOGY; CANCER CLASSIFICATION; CANCER RISK; CLINICAL FEATURE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; FEMALE; HIGH RISK POPULATION; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; INTERMETHOD COMPARISON; MAJOR CLINICAL STUDY; MALE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; THYROID NODULE;

ADULT; BIOPSY, NEEDLE; FEMALE; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; RISK; RISK ASSESSMENT; ROC CURVE; THYROID NEOPLASMS; THYROID NODULE;

EID: 11344280150     PISSN: 10507256     EISSN: None     Source Type: Journal    
DOI: 10.1089/thy.2004.14.1065     Document Type: Article

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