Supporting tools in psychiatric treatment decision-making: sertraline outcome investigation with artificial neural network method.
Controlled trials in clinical psychopharmacology may fail to provide reliable information about the benefit of treatment for the patient when considered in a real-life setting rather than as a part of a well-defined sampling procedure. Previously, we applied the mathematical model of an artificial neural network (ANN) to a pool of clinical information gathered through case descriptions provided by senior psychiatrists in clinical charts of patients receiving their first exposure to sertraline. In the present study, we applied the same mathematical model to a larger sample. The performance of the ANN model in forecasting successful and unsuccessful treatment showed an overall accuracy of classification of 97.12%. This result supports our previous finding about the potential application of this method as a reliable predictor of a given psychiatric patient's outcome during a specific psychopharmacological therapy.
Politi
Ernestina
E
Istituto Scientifico H. San Raffaele, Department of Neuropsychiatric Sciences, School of Medicine, Università Vita e Salute of Milan, Via Stamira d'Ancona 20, 20127 Milan, Italy. epoliti@tin.it
Franchini
Linda
L
Spagnolo
Chiara
C
Smeraldi
Enrico
E
Bellodi
Laura
L
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003657:Decision Making; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000628:therapy*; D008875:Middle Aged; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012494:Sampling Studies; D017367:Selective Serotonin Reuptake Inhibitors / Q000627:therapeutic use*; D020280:Sertraline / Q000627:therapeutic use*; D016896:Treatment Outcome
D017367:Selective Serotonin Reuptake Inhibitors; D020280:Sertraline