Standout Papers

Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP 2023 2026 202466
  1. Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP (2023)
    Rasheed Omobolaji Alabi, Mohammed Elmusrati et al. Scientific Reports

Immediate Impact

1 from Science/Nature 56 standout
Sub-graph 1 of 24

Citing Papers

Nanocarriers address intracellular barriers for efficient drug delivery, overcoming drug resistance, subcellular targeting and controlled release
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Advances and challenges in portable optical biosensors for onsite detection and point-of-care diagnostics
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2 intermediate papers

Works of Mohammed Elmusrati being referenced

Cancer Modeling‐on‐a‐Chip with Future Artificial Intelligence Integration
2019

Author Peers

Author Last Decade Papers Cites
Mohammed Elmusrati 321 294 351 54 1.2k
Ye Zhang 83 173 130 80 1.1k
Ijaz Ahmad 51 164 357 68 1.2k
Muzhou Hou 143 141 399 80 979
Dheyaa Ahmed Ibrahim 82 258 473 31 1.2k
Pau‐Choo Chung 58 222 465 91 1.3k
Sameem Abdul Kareem 106 178 374 66 1.2k
Keng Yeow Tay 105 61 259 32 905
Chaofeng Li 33 190 123 64 1.1k
Jun Jiang 45 282 254 57 968
Ji Wu 80 156 556 78 1.4k

All Works

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2026