Concordance networks and application to clustering cancer symptomology.
PLoS One
; 13(3): e0191981, 2018.
Article
em En
| MEDLINE
| ID: mdl-29538418
ABSTRACT
Symptoms of complex illnesses such as cancer often present with a high degree of heterogeneity between patients. At the same time, there are often core symptoms that act as common drivers for other symptoms, such as fatigue leading to depression and cognitive dysfunction. These symptoms are termed bridge symptoms and when combined with heterogeneity in symptom presentation, are difficult to detect using traditional unsupervised clustering techniques. This article develops a method for identifying patient communities based on bridge symptoms termed concordance network clustering. An empirical study of breast cancer symptomatology is presented, and demonstrates the applicability of this method for identifying bridge symptoms.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Modelos Biológicos
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article