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Patterns (New York, N.Y.)|December 26, 2022
Quantitative evaluation of explainable graph neural networks for molecular property predictionJiahua Rao, Shuangjia Zheng, Yutong Lu, et al.Patterns (New York, N.Y.)|December 26, 2022
Can counterfactual explanations of AI systems' predictions skew lay users' causal intuitions about the world? If so, can we correct for that?Marko Tešić, Ulrike HahnPatterns (New York, N.Y.)|May 24, 2022
Deep forecasting of translational impact in medical researchAmy P K Nelson, Robert J Gray, James K Ruffle, et al.Patterns (New York, N.Y.)|May 24, 2022
A fine-grained network for human identification using panoramic dental imagesHu Chen, Che Sun, Peixi Liao, et al.Patterns (New York, N.Y.)|May 24, 2022
Disrupting adversarial transferability in deep neural networksChristopher Wiedeman, Ge WangPatterns (New York, N.Y.)|May 24, 2022
Privacy-preserving federated neural network learning for disease-associated cell classificationSinem Sav, Jean-Philippe Bossuat, Juan R Troncoso-Pastoriza, et al.Patterns (New York, N.Y.)|July 21, 2021
Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inferenceMatthew Amodio, Dennis Shung, Daniel B Burkhardt, et al.Patterns (New York, N.Y.)|July 21, 2021
Structuring clinical text with AI: Old versus new natural language processing techniques evaluated on eight common cardiovascular diseasesXianghao Zhan, Marie Humbert-Droz, Pritam Mukherjee, et al.Patterns (New York, N.Y.)|July 21, 2021
Looking through glass: Knowledge discovery from materials science literature using natural language processingVineeth Venugopal, Sourav Sahoo, Mohd Zaki, et al.Patterns (New York, N.Y.)|July 21, 2021
The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systemsJann M Weinand, Russell McKenna, Max Kleinebrahm, et al.Pageof 92