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Analysis of Efficient Net Model Using Binary Segmentation Results from Magnetic Resonance Imaging (MRI) T1 Weighted Contrast Images in Classifying Brain Tumors Types.

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Title: Analysis of Efficient Net Model Using Binary Segmentation Results from Magnetic Resonance Imaging (MRI) T1 Weighted Contrast Images in Classifying Brain Tumors Types.
Authors: Ihtisyamuddin, Muhammad Alifian1 alifianimuhammad@gmail.com, Anwar, M. Choiroel1 choirul1960@gmail.com, Rasyid1 rasyid.lihawa@gmail.com, Kartikasari, Yeti1 yeti.kartikasari@gmail.com, Latifah, Leny1 leny003@brin.go.id, Wibowo, Gatot Murti1 gatotmurtiw@gmail.com
Source: International Journal of Social Health. Jul2025, Vol. 4 Issue 7, p357-364. 8p.
Database: Sociology Source Ultimate
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  Data: Analysis of Efficient Net Model Using Binary Segmentation Results from Magnetic Resonance Imaging (MRI) T1 Weighted Contrast Images in Classifying Brain Tumors Types.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Social+Health%22">International Journal of Social Health</searchLink>. Jul2025, Vol. 4 Issue 7, p357-364. 8p.
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      – Type: doi
        Value: 10.58860/ijsh.v4i7.311
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 357
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      – TitleFull: Analysis of Efficient Net Model Using Binary Segmentation Results from Magnetic Resonance Imaging (MRI) T1 Weighted Contrast Images in Classifying Brain Tumors Types.
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            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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            – TitleFull: International Journal of Social Health
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