Artificial neural networks can classify uninvestigated patients with dyspepsia

European Journal of Gastroenterology and Hepatology

Volumn 19, Issue 12, 2007, Pages 1055-1058

  Andriulli, Angelo ^a   Grossi, Enzo ^b   Buscema, Massimo ^c   Pilotto, Alberto ^a   Festa, Virginia ^a   Perri, Francesco ^a  

^a CASA SOLLIEVO DELLA SOFFERENZA HOSPITAL   (Italy)

^b Bracco Imaging SpA   (Italy)

^c Semeion centro ricerche di scienze della communicazione   (Italy)

Author keywords

Artificial intelligence; Artificial neural networks; Dyspepsia; H. pylori infection

Indexed keywords

ANAMNESIS; ARTIFICIAL NEURAL NETWORK; CLINICAL FEATURE; CLINICAL PROTOCOL; DATA BASE; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; DYSPEPSIA; FUNCTIONAL DISEASE; HUMAN; PRIORITY JOURNAL; REVIEW; RISK FACTOR; VALIDATION PROCESS;

DIAGNOSIS, COMPUTER-ASSISTED; DIAGNOSIS, DIFFERENTIAL; DYSPEPSIA; HELICOBACTER INFECTIONS; HELICOBACTER PYLORI; HUMANS; NEURAL NETWORKS (COMPUTER); PATIENT SELECTION;

EID: 36248951195     PISSN: 0954691X     EISSN: None     Source Type: Journal    
DOI: 10.1097/MEG.0b013e3282f198b2     Document Type: Review

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