ACM-CHIL
Member since:
2020-10-07
Last seen:
2020-12-14
User details
Name:
ACM Conference on Health, Inference, and Learning
Website:
https://www.chilconference.org/
About me:
The ACM Conference on Health, Inference, and Learning (ACM-CHIL), targets a cross-disciplinary representation of clinicians and researchers (from industry and academia) in machine learning, health policy, causality, fairness, and other related areas.
Papertalks of ACM-CHIL
23/07/2020
Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning
Niranjani Prasad, Barbara Engelhardt, Finale Doshi-Velez
Keywords Paper
Applied computing, Life and medical sciences, Health care information systems, Computing methodologies, Machine learning, Learning paradigms, Reinforcement learning, Sequential decision making, Learning settings, Batch learning
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7:45
23/07/2020
Variational learning of individual survival distributions
Zidi Xiu, Chenyang Tao, Ricardo Henao
Keywords Paper
Applied computing, Life and medical sciences, Health informatics, Computing methodologies, Modeling and simulation, Model development and analysis, Modeling methodologies
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0
0
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7:44
23/07/2020
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines
Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri and
Keywords Paper
Applied computing, Life and medical sciences, Health informatics, Mathematics of computing, Probability and statistics, Probabilistic representations, Bayesian networks, Causal networks
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7:57
23/07/2020
Adverse drug reaction discovery from electronic health records with deep neural networks
Wei Zhang, Zhaobin Kuang, Peggy Peissig, David Page
Keywords Paper
Applied computing, Life and medical sciences, Health informatics, Computing methodologies, Machine learning, Machine learning approaches, Neural networks
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0
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8:20
23/07/2020
CaliForest: calibrated random forest for health data
Yubin Park, Joyce C. Ho
Keywords Paper
Applied computing, Life and medical sciences, Health informatics, Computing methodologies, Machine learning, Machine learning algorithms, Ensemble methods, Bagging, Machine learning approaches, Classification and regression trees, General and reference, Cross-computing tools and techniques, Empirical studies
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7:46
23/07/2020
BMM-Net: automatic segmentation of edema in optical coherence tomography based on boundary detection and multi-scale network
Ruru Zhang, Jiawen He, Shenda Shi and
Keywords Paper
Applied computing, Life and medical sciences, Computational biology, Imaging, Computing methodologies, Artificial intelligence, Computer vision, Computer vision problems, Image segmentation, Computer vision tasks, Biometrics
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0
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9:45
23/07/2020
An adversarial approach for the robust classification of pneumonia from chest radiographs
Joseph D. Janizek, Gabriel Erion, Alex J. DeGrave, Su-In Lee
Keywords Paper
Applied computing, Life and medical sciences, Computing methodologies, Machine learning, Machine learning approaches, Learning latent representations, Neural networks
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8:07
23/07/2020
Disease state prediction from single-cell data using graph attention networks
Neal Ravindra, Arijit Sehanobish, Jenna L. Pappalardo and
Keywords Paper
Applied computing, Life and medical sciences, Computational biology, Computational transcriptomics, Computing methodologies, Machine learning, Machine learning algorithms, Feature selection, Machine learning approaches, Neural networks
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8:07
23/07/2020
MMiDaS-AE: multi-modal missing data aware stacked autoencoder for biomedical abstract screening
Eric W. Lee, Byron C. Wallace, Karla I. Galaviz, Joyce C. Ho
Keywords Paper
Applied computing, Life and medical sciences, Health informatics, Information systems, Information retrieval, Retrieval tasks and goals, Clustering and classification
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0
0
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7:52
23/07/2020
Interactive hybrid approach to combine machine and human intelligence for personalized rehabilitation assessment
Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic and
Keywords Paper
Applied computing, Life and medical sciences, Health care information systems, Human-centered computing, Human computer interaction (HCI), Interactive systems and tools, Theory of computation, Theory and algorithms for application domains, Machine learning theory, Reinforcement learning, Sequential decision making
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8:15
23/07/2020
TASTE: temporal and static tensor factorization for phenotyping electronic health records
Ardavan Afshar, Ioakeim Perros, Haesun Park and
Keywords Paper
Computing methodologies, Machine learning, Learning paradigms, Unsupervised learning, Dimensionality reduction and manifold learning
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7:55
23/07/2020
Analyzing the role of model uncertainty for electronic health records
Michael W. Dusenberry, Dustin Tran, Edward Choi and
Keywords Paper
Applied computing, Life and medical sciences, Computing methodologies, Machine learning, Machine learning approaches, Neural networks, Modeling and simulation, Model development and analysis, Uncertainty quantification
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8:18
