Publications

Journals

• Validation of a Deep Learning Algorithm for Continuous, Real‐Time Detection of Atrial Fibrillation Using a Wrist‐Worn Device in an Ambulatory Environment
  Ming‐Zher Poh, Anthony J. Battisti, Li-Fang Cheng, Janice Lin, Anil Patwardhan, Ganesh S. Venkataraman, Charles A. Athill, Nimesh S. Patel, Chinmay P. Patel, Christian E. Machado, Jeffrey T. Ellis, Lori A. Crosson, Yuriko Tamura, R. Scooter Plowman, Mintu P. Turakhia and Hamid Ghanbari, in Journal of the American Heart Association, 2023.[paper link]

• Sparse Multi-Output Gaussian Processes for Medical Time Series Prediction
  Li-Fang Cheng, Bianca Dumitrascu, Gregory Darnell, Corey Chivers, Michael Draugelis, Kai Li and Barbara Engelhardt, in BMC Medical Informatics and Decision Making, 2020. [paper link][code]

• Bayesian Nonparametric Discovery of Isoforms and Individual Specific Quantification
  Derek Aguiar, Li-Fang Cheng, Bianca Dumitrascu, Fantine Mordelet, Athma Pai and Barbara Engelhardt, in Nature Communications, 2018. [paper link][code]

Conferences

• Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes
  Li-Fang Cheng, Bianca Dumitrascu, Michael Zhang, Corey Chivers, Michael Draugelis, Kai Li and Barbara Engelhardt, in The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
  [paper link]
• An Optimal Policy for Patient Laboratory Tests in Intensive Care Units
  Li-Fang Cheng, Niranjani Prasad and Barbara Engelhardt, in Pacific Symposium on Biocomputing (PSB) 2019. arXiv:1808.04679. (*Equal contribution with Niranjani Prasad.)
• A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units
  Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, and Barbara Engelhardt, in Conference on Uncertainty in Artificial Intelligence (UAI), 2017. [paper link]
• Low-Power Multi-Processor System Architecture Design for Universal Biomedical Signal Processing
  Li-Fang Cheng, Tung-Chien Chen, and Liang-Gee Chen, in IEEE International Symposium on Circuits and Systems (ISCAS), 2013.
• Architecture Design of the Multi-functional Wavelet-based ECG Microprocessor for Realtime Detection of Abnormal Cardiac Events
  Li-Fang Cheng, Tung-Chien Chen, and Liang-Gee Chen, in IEEE International Engineering in Medicine and Biology Conference (EMBC), 2012.
• Density-based Hardware-oriented Classification for Spike Sorting Microsystems
  Li-Fang Cheng, Tung-Chien Chen, Nai-Fu Chang, and Liang-Gee Chen, in International IEEE/EMBS Conference on Neural Engineering (NER), 2011.

Abstract and Posters

• The Impact of Missing Data in User-Generated mHealth Time Series
  Li-Fang Cheng, David Stück, Tom Quisel, and Luca Foschini, in Machine Learning for Health Workshop, Neural Information Processing Systems (NIPS), 2017.
• Sparse Multi-Output Gaussian Processes for Medical Time Series Prediction
  Li-Fang Cheng, Gregory Darnell, Corey Chivers, Michael Draugelis, Kai Li and Barbara Engelhardt, in Machine Learning for Health Workshop, Neural Information Processing Systems (NIPS), 2016.
• BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification
  Derek Aguiar, Li-Fang Cheng, Bianca Dumitrascu, Fantine Mordelet and Barbara Engelhardt, in Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2016.
• A Temporal-Difference Approach with Unsupervised Data Imputation for Early Sepsis Prediction
  Li-Fang Cheng, Michael Draugelis, Kai Li and Barbara Engelhardt, in Machine Learning for Clinical Data Analysis, Healthcare and Genomics Workshop, Neural Information Processing Systems (NIPS), 2014.

Preprints and Unpublished Work

• Large Linear Multi-Output Gaussian Process Learning
  Vladimir Feinberg, Li-Fang Cheng, Kai Li and Barbara Engelhardt
  arXiv:1705.10813. Manuscript under review. [code]