A neural network approach to the outcome definition on first treatment with sertraline in a psychiatric population

L. Franchini, C. Spagnolo, D. Rossini, E. Smeraldi, L. Bellodi, E. Politi

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Therapy decision is one of the most important tasks clinicians have to perform in their clinical practice. The decision process requires taking into account many different factors. The Authors have proposed a neural computing approach for supporting clinical decision analysis. The mathematical model of artificial neural network (ANN) has been applied on a pool of clinical information gathered through case description freely filled by senior psychiatrists into 416 clinical charts. Sertraline, as drug for treatment, has been chosen since its clinical uses range from treatment of depression to that of many other psychiatric clinical conditions so that it has been thought to be a good candidate to this type of study. The ANN performance in forecasting successful and unsuccessful treatment cases showed an overall accuracy of classification of 97.35%. This result suggests a possible future application of this method to obtain a reliable prediction of a given psychiatric patient outcome during a specific psychopharmacological therapy, optimising the decisional making process.

Original languageEnglish
Pages (from-to)239-248
Number of pages10
JournalArtificial Intelligence in Medicine
Volume23
Issue number3
DOIs
Publication statusPublished - 2001

Fingerprint

Sertraline
Psychiatry
Neural networks
Population
Decision theory
Network performance
Therapeutics
Decision Support Techniques
Mathematical models
Theoretical Models
Depression
Pharmaceutical Preparations

Keywords

  • ANN
  • Psychiatry
  • Sertraline

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine(all)

Cite this

A neural network approach to the outcome definition on first treatment with sertraline in a psychiatric population. / Franchini, L.; Spagnolo, C.; Rossini, D.; Smeraldi, E.; Bellodi, L.; Politi, E.

In: Artificial Intelligence in Medicine, Vol. 23, No. 3, 2001, p. 239-248.

Research output: Contribution to journalArticle

Franchini, L. ; Spagnolo, C. ; Rossini, D. ; Smeraldi, E. ; Bellodi, L. ; Politi, E. / A neural network approach to the outcome definition on first treatment with sertraline in a psychiatric population. In: Artificial Intelligence in Medicine. 2001 ; Vol. 23, No. 3. pp. 239-248.
@article{d76f15fd43e14358a3ec47101329b54b,
title = "A neural network approach to the outcome definition on first treatment with sertraline in a psychiatric population",
abstract = "Therapy decision is one of the most important tasks clinicians have to perform in their clinical practice. The decision process requires taking into account many different factors. The Authors have proposed a neural computing approach for supporting clinical decision analysis. The mathematical model of artificial neural network (ANN) has been applied on a pool of clinical information gathered through case description freely filled by senior psychiatrists into 416 clinical charts. Sertraline, as drug for treatment, has been chosen since its clinical uses range from treatment of depression to that of many other psychiatric clinical conditions so that it has been thought to be a good candidate to this type of study. The ANN performance in forecasting successful and unsuccessful treatment cases showed an overall accuracy of classification of 97.35{\%}. This result suggests a possible future application of this method to obtain a reliable prediction of a given psychiatric patient outcome during a specific psychopharmacological therapy, optimising the decisional making process.",
keywords = "ANN, Psychiatry, Sertraline",
author = "L. Franchini and C. Spagnolo and D. Rossini and E. Smeraldi and L. Bellodi and E. Politi",
year = "2001",
doi = "10.1016/S0933-3657(01)00088-4",
language = "English",
volume = "23",
pages = "239--248",
journal = "Artificial Intelligence in Medicine",
issn = "0933-3657",
publisher = "Elsevier",
number = "3",

}

TY - JOUR

T1 - A neural network approach to the outcome definition on first treatment with sertraline in a psychiatric population

AU - Franchini, L.

AU - Spagnolo, C.

AU - Rossini, D.

AU - Smeraldi, E.

AU - Bellodi, L.

AU - Politi, E.

PY - 2001

Y1 - 2001

N2 - Therapy decision is one of the most important tasks clinicians have to perform in their clinical practice. The decision process requires taking into account many different factors. The Authors have proposed a neural computing approach for supporting clinical decision analysis. The mathematical model of artificial neural network (ANN) has been applied on a pool of clinical information gathered through case description freely filled by senior psychiatrists into 416 clinical charts. Sertraline, as drug for treatment, has been chosen since its clinical uses range from treatment of depression to that of many other psychiatric clinical conditions so that it has been thought to be a good candidate to this type of study. The ANN performance in forecasting successful and unsuccessful treatment cases showed an overall accuracy of classification of 97.35%. This result suggests a possible future application of this method to obtain a reliable prediction of a given psychiatric patient outcome during a specific psychopharmacological therapy, optimising the decisional making process.

AB - Therapy decision is one of the most important tasks clinicians have to perform in their clinical practice. The decision process requires taking into account many different factors. The Authors have proposed a neural computing approach for supporting clinical decision analysis. The mathematical model of artificial neural network (ANN) has been applied on a pool of clinical information gathered through case description freely filled by senior psychiatrists into 416 clinical charts. Sertraline, as drug for treatment, has been chosen since its clinical uses range from treatment of depression to that of many other psychiatric clinical conditions so that it has been thought to be a good candidate to this type of study. The ANN performance in forecasting successful and unsuccessful treatment cases showed an overall accuracy of classification of 97.35%. This result suggests a possible future application of this method to obtain a reliable prediction of a given psychiatric patient outcome during a specific psychopharmacological therapy, optimising the decisional making process.

KW - ANN

KW - Psychiatry

KW - Sertraline

UR - http://www.scopus.com/inward/record.url?scp=0034773012&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034773012&partnerID=8YFLogxK

U2 - 10.1016/S0933-3657(01)00088-4

DO - 10.1016/S0933-3657(01)00088-4

M3 - Article

C2 - 11704439

AN - SCOPUS:0034773012

VL - 23

SP - 239

EP - 248

JO - Artificial Intelligence in Medicine

JF - Artificial Intelligence in Medicine

SN - 0933-3657

IS - 3

ER -