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

Cassandra Heiselman

Cleveland Clinic

ORCID: 0000-0002-4027-1337

Also affiliated with Stony Brook University Hospital, Stony Brook 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 6%percentile
0.241Author 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.

Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women

2021 29th European Signal Processing Conference (EUSIPCO)(2021)10.23919/eusipco54536.2021.9616021
Top 61%
0.241DataRank
Top 61%4 citations

Cassandra Heiselman, Anna Fuchs, Mia A. Heiligenstein, Kimberly Herrera, Diana Garretto +2 more

Papers

Driven by 8 papers — median percentile 39. Top paper: “Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women”.

Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women

2021 29th European Signal Processing Conference (EUSIPCO)(2021)10.23919/eusipco54536.2021.9616021
Top 61%
0.241DataRank
Top 61%4 citations

Cassandra Heiselman, Anna Fuchs, Mia A. Heiligenstein, Kimberly Herrera, Diana Garretto +2 more

The impacts of the COVID-19 pandemic on birth satisfaction in a prospective cohort of 2,341 U.S. women

Women and Birth(2021)10.1016/j.wombi.2021.10.004
N/A
0DataRank · unranked
33 citations

Brittain Mahaffey, Cassandra Heiselman, Marci Lobel, Heidi Preis

Unsupervised Detection of Anomalies in Fetal Heart Rate Tracings using Phase Space Reconstruction

2021 29th European Signal Processing Conference (EUSIPCO)(2021)10.23919/eusipco54536.2021.9616264
N/A
0DataRank · unranked
3 citations

Marzieh Ajirak, Cassandra Heiselman, J. Gerald Quirk, Petar M. Djurić, Yang Liu

Characterizing Fetal Heart Rate From A State Space Perspective

2022 30th European Signal Processing Conference (EUSIPCO)(2022)10.23919/eusipco55093.2022.9909917
N/A
0DataRank · unranked
1 citations

Guanchao Feng, Cassandra Heiselman, J. Gerald Quirk, Petar M. Djurić, Tong Chen

Cardiotocography analysis by empirical dynamic modeling and Gaussian processes

Frontiers in Bioengineering and Biotechnology(2023)10.3389/fbioe.2022.1057807
N/A
0DataRank · unranked
4 citations

Cassandra Heiselman, J. Gerald Quirk, Petar M. Djurić, Guanchao Feng

Fetal Heart Rate Analysis from a Multi-task Learning Perspective with Gaussian Processes

(2023)10.23919/eusipco58844.2023.10289773
N/A
0DataRank · unranked
0 citations

Guanchao Feng, Cassandra Heiselman, J. Gerald Quirk, Petar M. Djurić, Tong Chen

Adverse Perinatal Outcomes Predicted by Prenatal Maternal Stress Among U.S. Women at the COVID-19 Pandemic Onset

Annals of Behavioral Medicine(2021)10.1093/abm/kaab005
N/A
0DataRank · unranked
85 citations

Brittain Mahaffey, Susmita Pati, Cassandra Heiselman, Marci Lobel, Heidi Preis

Fetal Well-Being Prediction with One-Class Gaussian Process Anomaly Detection

(2025)10.23919/eusipco63237.2025.11226585
N/A
0DataRank · unranked
0 citations

Cassandra Heiselman, Petar M. Djurić, Taraneh G. Azarnir