| Patients with Cancer Appear More Vulnerable to SARS-COV-2: A Multicenter Study during the COVID-19 Outbreak, M Dai, D Liu, M Liu, F Zhou, G Li, Z Chen, Z Zhang, H You, M Wu, Cancer discovery |
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| Expanded encyclopaedias of DNA elements in the human and mouse genomes, JE Moore, MJ Purcaro, HE Pratt, CB Epstein, N Shoresh, J Adrian, T Kawli, Nature 583 (7818), 699-710 |
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| Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records, L Huang, AL Shea, H Qian, A Masurkar, H Deng, D Liu Journal of biomedical informatics 99, 103291 |
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| The role of absolute humidity on transmission rates of the COVID-19 outbreak, W Luo, MS Majumder, D Liu, C Poirier, KD Mandl, M Lipsitch, MedRxiv, 2020.02. 12.20022467 |
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| LoAdaBoost: Loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data, L Huang, Y Yin, Z Fu, S Zhang, H Deng, D Liu, Plos one 15 (4), e0230706 |
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| A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models, D Liu, L Clemente, C Poirier, X Ding, M Chinazzi, JT Davis, A Vespignani, arXiv preprint arXiv:2004.04019 |
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| The role of environmental factors on transmission rates of the COVID-19 outbreak: an initial assessment in two spatial scales, C Poirier, W Luo, MS Majumder, D Liu, KD Mandl, TA Mooring, Scientific reports 10 (1), 17002 |
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| Perspectives on ENCODE, MP Snyder, TR Gingeras, JE Moore, Z Weng, MB Gerstein, B Ren, Nature 583 (7818), 693-698 |
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| FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record, D Liu, T Miller, R Sayeed, K Mandl, NIPS Machine Learning for Health (ML4H) Workshop |
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| Two-stage federated phenotyping and patient representation learning, D Liu, D Dligach, T Miller, Proceedings of the 18th BioNLP Workshop |
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| DeepFaceLIFT: interpretable personalized models for automatic estimation of self-reported pain, D Liu, F Peng, A Shea, R Picard, Journal of Machine Learning Research 66, 1-16 |
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| Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models, D Liu, L, Clemente, C Poirier, X Ding, M Chinazzi, J Davis, A Vespignani, Journal of medical Internet research 22 (8), e20285 |
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| High-throughput 5′ UTR engineering for enhanced protein production in non-viral gene therapies, J Cao, EM Novoa, Z Zhang, WCW Chen, D Liu, GCG Choi, ASL Wong, Nature communications 12 (1), 4138 |
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| Maintenance of distinct melanocyte populations in the interfollicular epidermis, JD Glover, S Knolle, KL Wells, D Liu, IJ Jackson, RL Mort, DJ Headon, Pigment Cell & Melanoma Research 28 (4), 476-480 |
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| Discrete-valued neural communication, D Liu, AM Lamb, K Kawaguchi, AG ALIAS PARTH GOYAL, C Sun, Advances in Neural Information Processing Systems 34, 2109-2121 |
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| Flow: A dataset and benchmark for floating waste detection in inland waters, Y Cheng, J Zhu, M Jiang, J Fu, C Pang, P Wang, K Sankaran, O Onabola, Proceedings of the IEEE/CVF International Conference on Computer Vision … |
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| Federated pretraining and fine tuning of bert using clinical notes from multiple silos, D Liu, T Miller, arXiv preprint arXiv:2002.08562 |
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| Machine learning methods for automatic pain assessment using facial expression information: Protocol for a systematic review and meta-analysis, D Liu, D Cheng, TT Houle, L Chen, W Zhang, H Deng, Medicine 97 (49) |
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| Genie: a secure, transparent sharing and services platform for genetic and health data, S Zhang, A Kim, D Liu, SC Nuckchady, L Huang, A Masurkar, J Zhang, arXiv preprint arXiv:1811.01431 |
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| FeARH: Federated machine learning with anonymous random hybridization on electronic medical records, J Cui, H Zhu, H Deng, Z Chen, D Liu, Journal of Biomedical Informatics 117, 103735 |
