New approach to predicting proconvulsant activity with the use of Support Vector Regression

Computers in Biology and Medicine

Volumn 42, Issue 5, 2012, Pages 575-581

  Salat, Robert ^a   Salat, Kinga ^b  

^a WARSAW UNIVERSITY OF LIFE SCIENCES   (Poland)

^b JAGIELLONIAN UNIVERSITY   (Poland)

Author keywords

Antiepileptic drugs; Maximal electroshock seizure threshold; Neurotoxicity; Support Vector Regression

Indexed keywords

ANIMAL MODEL; ANTICONVULSANT ACTIVITY; ANTIEPILEPTIC DRUGS; BIPOLAR DISORDER; DOSE RANGE; IN-VIVO; LIVING ANIMALS; MATHEMATICAL METHOD; MAXIMAL ELECTROSHOCK SEIZURES; NEUROPATHIC PAIN; NEUROTOXICITY; REGRESSION MODE; SCREENING PROCESS; SUPPORT VECTOR MACHINE (SVM); SUPPORT VECTOR REGRESSION; SUPPORT VECTOR REGRESSION (SVR); THERAPEUTIC DOSE; TOXIC EFFECT;

DIAGNOSIS; INDUSTRIAL POISONS; MATHEMATICAL MODELS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; TOXICITY;

FORECASTING;

ANTICONVULSIVE AGENT; CONVULSANT AGENT;

ANIMAL EXPERIMENT; ANTICONVULSANT ACTIVITY; ARTICLE; CONTROLLED STUDY; CONVULSION; IN VIVO STUDY; MALE; MOUSE; NONHUMAN; PREDICTION; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

ANIMALS; CONVULSANTS; MALE; MICE; REGRESSION ANALYSIS; SEIZURES; SUPPORT VECTOR MACHINES;

ANIMALIA; MUS;

EID: 84859216529     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2012.02.001     Document Type: Article

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