Unknown

Dataset Information

0

Concordance networks and application to clustering cancer symptomology.


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.

SUBMITTER: Henry TR 

PROVIDER: S-EPMC5851541 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

altmetric image

Publications

Concordance networks and application to clustering cancer symptomology.

Henry Teague R TR   Marshall Sarah A SA   Avis Nancy E NE   Levine Beverly J BJ   Ip Edward H EH  

PloS one 20180314 3


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 identifyin  ...[more]

Similar Datasets

| S-EPMC7108968 | biostudies-literature
| S-EPMC9250294 | biostudies-literature
| S-EPMC7953862 | biostudies-literature
| S-EPMC8754433 | biostudies-literature
| S-EPMC3313482 | biostudies-literature
| S-EPMC4650685 | biostudies-literature
| S-EPMC8166179 | biostudies-literature
| S-EPMC8237321 | biostudies-literature
| S-EPMC5863042 | biostudies-literature
| S-EPMC3392237 | biostudies-literature