Predicting the effectiveness of hydroxyurea in individual sickle cell anemia patients

Artificial Intelligence in Medicine

Volumn 18, Issue 2, 2000, Pages 133-148

  Valafar, Homayoun ^a   Valafar, Faramarz ^a   Darvill, Alan ^a   Albersheim, Peter ^a   Kutlar, Abdullah ^b   Woods, Kristy F ^b   Hardin, John ^b  

^a UNIVERSITY OF GEORGIA   (United States)

^b MEDICAL COLLEGE OF GEORGIA   (United States)

Author keywords

Artificial neural networks; Hydrea; Hydroxyurea; Pattern recognition; Sickle cell anemia; Variable selection

Indexed keywords

CORRELATION METHODS; DISEASES; HEMOGLOBIN; NEURAL NETWORKS; NITROGEN COMPOUNDS; PATIENT TREATMENT; PATTERN RECOGNITION; REGRESSION ANALYSIS; STATISTICAL TESTS;

HYDREA; HYDROXYUREA; SICKLE CELL ANEMIA;

MEDICAL COMPUTING;

HEMOGLOBIN F; HYDROXYUREA;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLINICAL TRIAL; DRUG EFFICACY; ERYTHROCYTE; FEMALE; HUMAN; HUMAN TISSUE; MAJOR CLINICAL STUDY; MALE; MEAN CORPUSCULAR VOLUME; PATTERN RECOGNITION; PRIORITY JOURNAL; PROGNOSIS; REGRESSION ANALYSIS; SICKLE CELL ANEMIA;

ADOLESCENT; ANEMIA, SICKLE CELL; ERYTHROCYTE VOLUME; FEMALE; FETAL HEMOGLOBIN; HUMANS; HYDROXYUREA; MALE; NEURAL NETWORKS (COMPUTER);

EID: 0033966322     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0933-3657(99)00035-4     Document Type: Article

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