Pattern classification as decision support tool in antipsychotic treatment algorithms.
Exp Neurol
; 339: 113635, 2021 05.
Article
in En
| MEDLINE
| ID: mdl-33548218
ABSTRACT
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Psychotic Disorders
/
Antipsychotic Agents
/
Algorithms
/
Machine Learning
Type of study:
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Exp Neurol
Year:
2021
Document type:
Article
Affiliation country: