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Diagnostic performance of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.

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Title: Diagnostic performance of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.
Authors: Zhang, Kun1 (AUTHOR), Zhou, Xin2 (AUTHOR), Zhang, Yuhang1 (AUTHOR), Jin, Gang1 (AUTHOR), Li, Ping1 (AUTHOR), Xing, Yuzhuo1 (AUTHOR) xyzmahw@163.com
Source: PLoS ONE. 7/6/2026, Vol. 21 Issue 7, p1-11. 11p.
Database: Academic Search Ultimate
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  Data: Diagnostic performance of machine learning models based on dual-phase <superscript>99</superscript>mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 7/6/2026, Vol. 21 Issue 7, p1-11. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=195125672
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        Value: 10.1371/journal.pone.0353271
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        Text: English
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      – TitleFull: Diagnostic performance of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.
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              Text: 7/6/2026
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              Y: 2026
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