Hannah P. Cowley

发表

Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets

Luis M. Rodriguez, Theodore J. LaGrow, Erik C. Johnson, 2020, GigaScience.

Using Machine Learning to Discover Unexpected Patterns in Clinical Data: A Case Study in COVID-19 Sub-cohort Discovery

Jordan K. Matelsky, S. Zeger, Hannah P. Cowley, 2022 .

Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients

Jordan K. Matelsky, Hannah P. Cowley, William Gray-Roncal, 2023, Scientific Reports.

A framework for rigorous evaluation of human performance in human and machine learning comparison studies

Timothy M. Shead, Frances S. Chance, Brock Andrew Wester, 2022, Scientific Reports.

A Saliva-Based Serological and Behavioral Analysis of SARS-CoV-2 Antibody Prevalence in Howard County, Maryland

Shraddha V. Patel, Phillip T. Koshute, Hannah P. Cowley, 2023, Microbiology spectrum.

Benchmarking Human Performance for Visual Search of Aerial Images

Brock Andrew Wester, Rebecca E. Rhodes, B. Wester, 2021, Frontiers in Psychology.

Author Correction: A framework for rigorous evaluation of human performance in human and machine learning comparison studies

Timothy M. Shead, Frances S. Chance, Rebecca E. Rhodes, 2022, Scientific Reports.

Toward A Reproducible, Scalable Framework for Processing Large Neuroimaging Datasets

Jordan Matelsky, Eva L. Dyer, Konrad P. Kording, 2019, bioRxiv.

A substrate for modular, extensible data-visualization

Jordan Matelsky, Brock A. Wester, Jordan K. Matelsky, 2017, bioRxiv.