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Patterns (New York, N.Y.)|November 25, 2021
TDAExplore: Quantitative analysis of fluorescence microscopy images through topology-based machine learningParker Edwards, Kristen Skruber, Nikola Milićević, et al.Patterns (New York, N.Y.)|January 29, 2021
The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere AccordGordon S Blair, Richard Bassett, Lucy Bastin, et al.Patterns (New York, N.Y.)|January 29, 2021
Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy ActJoris Dehler-Holland, Kira Schumacher, Wolf FichtnerPatterns (New York, N.Y.)|January 29, 2021
The Bird Is Not the Migration Data: Insights from an Artwork Exploring Machine-Animal CollaborationEryk SalvaggioPatterns (New York, N.Y.)|January 29, 2021
How Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared?Priyanka PillaiPatterns (New York, N.Y.)|March 22, 2021
The risk of re-identification remains high even in country-scale location datasetsAli Farzanehfar, Florimond Houssiau, Yves-Alexandre de MontjoyePatterns (New York, N.Y.)|March 22, 2021
Taking a fresh look at FAIR for research softwareDaniel S Katz, Morane Gruenpeter, Tom HoneymanPatterns (New York, N.Y.)|February 16, 2022
Sequencing meets machine learning to fight emerging pathogens: A previewArtur YakimovichPatterns (New York, N.Y.)|October 25, 2021
Creating ethics guidelines for artificial intelligence and big data analytics customers: The case of the consumer European insurance marketMartin Mullins, Christopher P Holland, Martin CunneenPatterns (New York, N.Y.)|April 25, 2022
Shapley variable importance cloud for interpretable machine learningYilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, et al.Pageof 92