🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Kaida Ning

Peng Cheng Laboratory

ORCID: 0000-0002-9223-2014

Biochemistry, Genetics and Molecular BiologyNeuroscienceMedicine

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 3 papers. Top paper: “Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging”.

Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging

Neurobiology of Aging(2021)10.1016/j.neurobiolaging.2021.03.014

N/A

0.550DataRank · unranked

38 citations

Ben A. Duffy, Meredith Franklin, William Matloff, Lu Zhao, Nibal Arzouni +3 more

Association of relative brain age with tobacco smoking, alcohol consumption, and genetic variants

Scientific Reports(2020)10.1038/s41598-019-56089-4

N/A

0DataRank · unranked

163 citations

Lu Zhao, William Matloff, Fengzhu Sun, Arthur W. Toga, Kaida Ning

Characterizing brain imaging features associated with ADAS-Cog13 sub-scores with 3D convolutional neural networks

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.03.17.484832

N/A

0DataRank · unranked

3 citations

Pascale B. Cannon, Jiawei Yu, Srinesh Shenoi, Lu Wang, Alzheimer’s Disease Neuroimaging Initiative +2 more