Additional file 2 of Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical analysis better?

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Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29926627
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Additional file 2 of Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical analysis better?

Figshare
Pregnancy and preeclampsia studies
article

Additional file 2 of Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical analysis better?

article en

Abstract

No abstract available for this paper.
Figshare
University of Illinois Chicago (US), Kaohsiung Chang Gung Memorial Hospital (TW), China Medical University (CN)
Openalex Percentile: Top 38%
Pregnancy and preeclampsia studies
DOIOpen Access PDFOpenAlex
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Additional file 2 of Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical analysis better? · Figshare (2025) | TGRS Research Map | TGRS