Diagnostic Accuracy of Machine-Learning Models on Predicting Chemo-Brain in Breast Cancer Survivors Previously Treated with Chemotherapy: A Meta-Analysis.
breast cancer
chemo-brain
chemotherapy
diagnostic accuracy
machine learning
Journal
International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455
Informations de publication
Date de publication:
15 12 2022
15 12 2022
Historique:
received:
15
11
2022
revised:
11
12
2022
accepted:
12
12
2022
entrez:
23
12
2022
pubmed:
24
12
2022
medline:
27
12
2022
Statut:
epublish
Résumé
We performed a meta-analysis of chemo-brain diagnostic, pooling sensitivities, and specificities in order to assess the accuracy of a machine-learning (ML) algorithm in breast cancer survivors previously treated with chemotherapy. We searched PubMed, Web of Science, and Scopus for eligible articles before 30 September 2022. We identified three eligible studies from which we extracted seven ML algorithms. For our data, the χ
Identifiants
pubmed: 36554712
pii: ijerph192416832
doi: 10.3390/ijerph192416832
pmc: PMC9779296
pii:
doi:
Types de publication
Meta-Analysis
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
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