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Nisha Bansal

Researcher at University of Washington

Publications -  154
Citations -  6509

Nisha Bansal is an academic researcher from University of Washington. The author has contributed to research in topics: Kidney disease & Medicine. The author has an hindex of 28, co-authored 111 publications receiving 3145 citations. Previous affiliations of Nisha Bansal include University of Washington Medical Center & Seattle University.

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From Local Explanations to Global Understanding with Explainable AI for Trees.

TL;DR: An explanation method for trees is presented that enables the computation of optimal local explanations for individual predictions, and the authors demonstrate their method on three medical datasets.

A catalog of genetic loci associated with kidney function from analyses of a million individuals

Matthias Wuttke, +327 more
TL;DR: Trans-ancestry meta-analysis of estimated glomerular filtration rate (eGFR) from 1,046,070 individuals identifies 264 associated loci, providing a resource of molecular targets for translational research of chronic kidney disease.
Journal ArticleDOI

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels

Adrienne Tin, +251 more
- 01 Oct 2019 - 
TL;DR: A trans-ancestry genome-wide association study of serum urate levels identifies 183 loci that improve the prediction of gout in an independent cohort of 334,880 individuals, and implicates the kidney and liver as key target organs and prioritize potential causal genes.
Posted Content

Explainable AI for Trees: From Local Explanations to Global Understanding

TL;DR: Improvements to the interpretability of tree-based models through the first polynomial time algorithm to compute optimal explanations based on game theory, and a new type of explanation that directly measures local feature interaction effects.