2017
DOI: 10.1007/s11136-017-1760-9
|View full text |Cite
|
Sign up to set email alerts
|

Clustering based on unsupervised binary trees to define subgroups of cancer patients according to symptom severity in cancer

Abstract: Our study suggests that CUBT is relevant to define the levels of symptom severity in cancer. This finding may have important implications for helping clinicians to interpret symptom profiles in clinical practice, to identify individuals at risk for poorer outcomes and implement targeted interventions.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2020
2020

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 35 publications
0
1
0
Order By: Relevance
“…Patient-generated data are a largely underused asset that can bring additional information to clinical practice by increasing inclusion from patients without access to clinical trials and by informing oncologists about health influences, including variables like physical activity, diet, and blood pressure-each of which is patient-reportable and often overlooked. 153,154 In an ideal scenario, results obtained from various sources (medical history, genomics, proteomics, metabolomics, clinical trial, patient input, etc) would be validated and combined to allow physicians to stratify patients using sensitive and specific screening algorithms.…”
Section: Knowledge Gap and Challengesmentioning
confidence: 99%
“…Patient-generated data are a largely underused asset that can bring additional information to clinical practice by increasing inclusion from patients without access to clinical trials and by informing oncologists about health influences, including variables like physical activity, diet, and blood pressure-each of which is patient-reportable and often overlooked. 153,154 In an ideal scenario, results obtained from various sources (medical history, genomics, proteomics, metabolomics, clinical trial, patient input, etc) would be validated and combined to allow physicians to stratify patients using sensitive and specific screening algorithms.…”
Section: Knowledge Gap and Challengesmentioning
confidence: 99%