Novel classification of acute liver failure through clustering using a self-organizing map: Usefulness for prediction of the outcome

Journal of Gastroenterology

Volumn 46, Issue 9, 2011, Pages 1127-1135

  Nakayama, Nobuaki ^a   Oketani, Makoto ^b   Kawamura, Yoshihiro ^c   Inao, Mie ^a   Nagoshi, Sumiko ^a   Fujiwara, Kenji ^d   Tsubouchi, Hirohito ^b   Mochida, Satoshi ^a  

^a SAITAMA MEDICAL UNIVERSITY   (Japan)

^b KAGOSHIMA UNIVERSITY   (Japan)

^c IBM JAPAN LTD   (Japan)

^d YOKOHAMA ROSAI HOSPITAL   (Japan)

Author keywords

Artificial neural network; Data mining; Fulminant hepatitis; Hepatic encephalopathy; Liver transplantation

Indexed keywords

ACUTE LIVER FAILURE; ADULT; ARTICLE; BRAIN DISEASE; CLUSTER ANALYSIS; CONSERVATIVE TREATMENT; CONTROLLED STUDY; DISEASE CLASSIFICATION; FEMALE; HEPATITIS; HUMAN; INCIDENCE; LIVER TRANSPLANTATION; MAJOR CLINICAL STUDY; MALE; PREDICTION; PRIORITY JOURNAL; SURVIVAL RATE; SYMPTOM; VALIDITY;

ADULT; AGED; CLUSTER ANALYSIS; DATA COLLECTION; DISEASE PROGRESSION; FEMALE; HEPATIC ENCEPHALOPATHY; HEPATITIS; HUMANS; JAPAN; LIVER FAILURE, ACUTE; LIVER TRANSPLANTATION; MALE; MIDDLE AGED; OUTCOME ASSESSMENT (HEALTH CARE); SURVIVAL RATE; TIME FACTORS;

EID: 80755190058     PISSN: 09441174     EISSN: 14355922     Source Type: Journal    
DOI: 10.1007/s00535-011-0420-z     Document Type: Article

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