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

Andrew M. Naidech

Northwestern University

ORCID: 0000-0003-1065-5417

Also affiliated with Northwestern University

Medicine

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 5%percentile
0.407Author DataRank

Indexed papers

1in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system

Learning Health Systems(2024)10.1002/lrh2.10417
Top 45%
0.407DataRank
Top 45%10 citations

Chengsheng Mao, L. Nelson Sanchez‐Pinto, Faraz S. Ahmad, Andrew M. Naidech, Luke V. Rasmussen +29 more

Papers

Driven by 22 papers — median percentile 55. Top paper: “The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform”.

The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform

ACI Open(2021)10.1055/s-0041-1731004
N/A
8.0DataRank · unranked
117 citations

Adam Frees, Steven Honeywell, Courtney Huang, Andrew M. Naidech, Jason H. Moore +2 more

National Institutes of Health StrokeNet During the Time of COVID-19 and Beyond

Stroke(2020)10.1161/strokeaha.120.030417
N/A
0.464DataRank · unranked
21 citations

Jordan Elm, L. Scott Janis, Wenle Zhao, Claudia S. Moy, Catherine Dillon +34 more

Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system

Learning Health Systems(2024)10.1002/lrh2.10417
Top 45%
0.407DataRank
Top 45%10 citations

Chengsheng Mao, L. Nelson Sanchez‐Pinto, Faraz S. Ahmad, Andrew M. Naidech, Luke V. Rasmussen +29 more

Hypocapnia, ischemic lesions, and outcomes after intracerebral hemorrhage

Journal of the Neurological Sciences(2020)10.1016/j.jns.2020.117139
N/A
0.396DataRank · unranked
13 citations

Jatinder S. Minhas, Eric M. Liotta, Farzaneh A. Sorond, Andrew M. Naidech, Matthew B. Maas +1 more

Serum osmolality, cerebrospinal fluid specific gravity and overt hepatic encephalopathy severity in patients with liver failure

Liver International(2020)10.1111/liv.14400
N/A
0.360DataRank · unranked
10 citations

Constantine Karvellas, Minjee Kim, Ayush Batra, Andrew M. Naidech, Shyam Prabhakaran +4 more

Effect of Magnesium on Deterioration and Symptomatic Hemorrhagic Transformation in Cerebral Ischemia: An Ancillary Analysis of the FAST-MAG Trial

Cerebrovascular Diseases(2023)10.1159/000528385
N/A
0.189DataRank · unranked
2 citations

Michael Jang, May Kim‐Tenser, Kristina Shkirkova, David S. Liebeskind, Sidney Starkman +7 more

Antiplatelet Medications and Biomarkers of Hemostasis May Explain the Association of Hematoma Appearance and Subsequent Hematoma Expansion After Intracerebral Hemorrhage

Neurocritical Care(2021)10.1007/s12028-021-01369-z
N/A
0.165DataRank · unranked
2 citations

Hye Jung Shin, William Metcalf-Doetsch, Yuan Luo, Paul F. Lindholm, Hau C. Kwaan +2 more

Predicting Early Seizures After Intracerebral Hemorrhage with Machine Learning

Neurocritical Care(2022)10.1007/s12028-022-01470-x
N/A
0DataRank · unranked
26 citations

Julianne Murphy, Katharine Colton, Hanyin Wang, Hye Jung Shin, Roland Faigle +2 more

Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants

BMC Medical Informatics and Decision Making(2022)10.1186/s12911-022-01871-0
N/A
0DataRank · unranked
25 citations

Yikuan Li, Andrew M. Naidech, Yuan Luo, Hanyin Wang

Patterns of diverse and changing sentiments towards COVID-19 vaccines: a sentiment analysis study integrating 11 million tweets and surveillance data across over 180 countries

Journal of the American Medical Informatics Association(2023)10.1093/jamia/ocad029
N/A
0DataRank · unranked
10 citations

Yikuan Li, Meghan R. Hutch, Adrienne S Kline, Sebastián Otero, Leena B. Mithal +4 more

Blood pressure medication and acute kidney injury after intracerebral haemorrhage: an analysis of the ATACH-II trial

BMJ Neurology Open(2023)10.1136/bmjno-2023-000458
N/A
0DataRank · unranked
5 citations

Hanyin Wang, Meghan R. Hutch, Julianne Murphy, James Paparello, Philip M. Bath +3 more

Fixed- Versus Variable-Dose Prothrombin Complex Concentrate for the Emergent Reversal of Vitamin K Antagonists: A Systematic Review and Meta-Analysis

Critical Care Medicine(2024)10.1097/ccm.0000000000006212
N/A
0DataRank · unranked
10 citations

Matthew B. Maas, Andrew M. Naidech, Babak S. Jahromi, Matthew B. Potts, Amr Alwakeal

Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes

Neurocritical Care(2024)10.1007/s12028-024-02067-2
N/A
0DataRank · unranked
3 citations

Juliana Silva Pinheiro do Nascimento, Ethan J. Houskamp, Hanyin Wang, Meghan R. Hutch, Yuzhe Liu +3 more

Patient and clinician perspectives in the use of machine learning and artificial intelligence in the context of acute neurology

JAMIA Open(2025)10.1093/jamiaopen/ooaf143
N/A
0DataRank · unranked
2 citations

Ethan J. Houskamp, Juliana Silva Pinheiro do Nascimento, Elaf Agha, William K. Thompson, Kelly N. Michelson +2 more

Natural History of Infratentorial Intracerebral Hemorrhages: Two Subgroups with Distinct Presentations and Outcomes

Journal of Stroke and Cerebrovascular Diseases(2020)10.1016/j.jstrokecerebrovasdis.2020.104920
N/A
0DataRank · unranked
21 citations

Roxanna M. García, Dionne Swor, Eric M. Liotta, Matthew B. Maas, Andrew M. Naidech +1 more

Thromboelastography may assess the effect of anticoagulation reversal in intracranial hemorrhage

Journal of Stroke and Cerebrovascular Diseases(2025)10.1016/j.jstrokecerebrovasdis.2025.108228
N/A
0DataRank · unranked
3 citations

BA Faine, Mohammed Ghannam, HM Olalde, Linder Wendt, Andrew M. Naidech +3 more

Why Physicians Prescribe Prophylactic Seizure Medications after Intracerebral Hemorrhage: An Adaptive Conjoint Analysis

Journal of Stroke and Cerebrovascular Diseases(2020)10.1016/j.jstrokecerebrovasdis.2019.104628
N/A
0DataRank · unranked
16 citations

Shyam Prabhakaran, Elizabeth Tipton, Andrew M. Naidech, Daniel Pinto

Trade-Offs in Quality-of-Life Assessment Between the Modified Rankin Scale and Neuro-QoL Measures

Value in Health(2020)10.1016/j.jval.2020.06.011
N/A
0DataRank · unranked
10 citations

Carmen Capo‐Lugo, Rajbeer Singh Sangha, Andrew M. Naidech, Shyam Prabhakaran, Robert L. Askew

Differential Effects of Time to Initiation of Therapy on Disability and Quality of Life in Patients With Mild and Moderate to Severe Ischemic Stroke

Archives of Physical Medicine and Rehabilitation(2020)10.1016/j.apmr.2020.05.005
N/A
0DataRank · unranked
8 citations

Carmen Capo‐Lugo, Andrew M. Naidech, Shyam Prabhakaran, Robert L. Askew

Elevated Cerebrospinal Fluid Protein Is Associated with Unfavorable Functional Outcome in Spontaneous Subarachnoid Hemorrhage

Journal of Stroke and Cerebrovascular Diseases(2020)10.1016/j.jstrokecerebrovasdis.2019.104605
N/A
0DataRank · unranked
17 citations

Matthew B. Maas, Ayush Batra, Minjee Kim, Edward M. Manno, Farzaneh A. Sorond +4 more

Identifying Modifiable Predictors of Patient Outcomes After Intracerebral Hemorrhage with Machine Learning

Neurocritical Care(2020)10.1007/s12028-020-00982-8
N/A
0DataRank · unranked
35 citations

Bradley W. Weaver, Eric M. Liotta, Matthew B. Maas, Roland Faigle, Daniel K. Mroczek +2 more

Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study (Preprint)

(2020)10.2196/preprints.26302
N/A
0DataRank · unranked
1 citations

Yikuan Li, Meghan R. Hutch, Andrew M. Naidech, Yuan Luo, Hanyin Wang