Expression of Concern: Imbalanced class distribution and performance evaluation metrics: A systematic review of prediction accuracy for determining model performance in healthcare systems
Abstract
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsArtificial Intelligence in Healthcare · Healthcare Systems and Reforms · Imbalanced Data Classification Techniques
The PLOS Digital Health Editors issue this Expression of Concern to inform readers of the following issues that came to light after this article’s [1] publication.
Supporting information
S1 FilePRISMA checklist.(DOCX)
S2 FileStandardized data extraction form.(DOCX)
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Owusu-Adjei M, Ben Hayfron-Acquah J, Frimpong T, Abdul-Salaam G. Imbalanced class distribution and performance evaluation metrics: A systematic review of prediction accuracy for determining model performance in healthcare systems. PLOS Digit Health. 2023;2(11):e 0000290. doi: 10.1371/journal.pdig.0000290 38032863 PMC 10688675 · doi ↗ · pubmed ↗
- 2Karthick K, Aruna SK, Samikannu R, Kuppusamy R, Teekaraman Y, Thelkar AR. Implementation of a Heart Disease Risk Prediction Model Using Machine Learning. Comput Math Methods Med. 2022;2022:6517716. doi: 10.1155/2022/6517716 35547562 PMC 9085310 · doi ↗ · pubmed ↗
- 3Methods In Medicine CAM. Retracted: Implementation of a Heart Disease Risk Prediction Model Using Machine Learning. Comput Math Methods Med. 2023;2023:9764021. doi: 10.1155/2023/9764021 37503437 PMC 10371591 · doi ↗ · pubmed ↗
- 4Mehbodniya A, Alam I, Pande S, Neware R, Rane KP, Shabaz M, et al. Financial Fraud Detection in Healthcare Using Machine Learning and Deep Learning Techniques. Security and Communication Networks. 2021;2021:1–8. doi: 10.1155/2021/9293877 · doi ↗
- 5Retracted: Financial Fraud Detection in Healthcare Using Machine Learning and Deep Learning Techniques. Security and Communication Networks. 2023;2023:1–1. doi: 10.1155/2023/9758612 · doi ↗