Predictive Model Explanation
Predictive Model Explanation is a computational methodology that belongs to the class of interpretability techniques in multi-omics research, distinguished by its capacity to elucidate the mechanistic basis of predictions generated by integrative models through feature attribution, pathway enrichment, or network-based reasoning.
84
Publications
7.7K
Citations
293
Authors
157
Institutions
Publications per year
2017–2026
62
Parents
84
Why significant variables aren’t automatically good predictors
Adeline Lo, Herman Chernoff, Tian Zheng et al. · Proceedings of the National Academy of Sciences · 2015 · 313 citations · Full text
Explainable AI for Trees: From Local Explanations to Global Understanding
Scott Lundberg, Gabriel Erion, Hugh Chen et al. · arXiv (Cornell University) · 2019 · 263 citations · Full text
Faithful and Customizable Explanations of Black Box Models
Himabindu Lakkaraju, Ece Kamar, Rich Caruana et al. · 2019 · 262 citations · Full text
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Harvard University
Cambridge, United States
3 h-index
3 publications
832 citations
University of Washington
Seattle, United States
3 h-index
5 publications
436 citations
University of Lisbon
Lisbon, Portugal
3 h-index
7 publications
125 citations

Mansoura University
Al Mansurah, Egypt
2 h-index
3 publications
76 citations

Drexel University
Philadelphia, United States
2 h-index
4 publications
689 citations
Universität Ulm
Ulm, Germany
2 h-index
4 publications
106 citations
University of Mons
Mons, Belgium
2 h-index
6 publications
147 citations
Warsaw University of Technology
Warsaw, Poland
2 h-index
3 publications
291 citations
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Repository · 15 publications · 814 citations
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2 publications · 118 citations
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2 publications · 63 citations
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2 publications · 105 citations
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2 publications · 34 citations
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