Joshua Charles Denny
Genetics · 2003–2019
A researcher in the Science corpus: 39 papers; trusts 36 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Genetics — 167 citations into it; #2,422 of 6,854 by trust here, #407 by citations
- Molecular Biology — 135 citations into it; #1,865 of 17,773 by trust here, #2,201 by citations
- Artificial Intelligence — 105 citations into it; #6,952 of 35,345 by trust here, #4,393 by citations
- Health Information Management — 45 citations into it; #333 of 344 by trust here, #37 by citations
- Public Health, Environmental and Occupational Health — 41 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it
- Cancer Research — 24 citations into it
- Immunology — 24 citations into it
Whom Joshua Charles Denny trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alan R. Aronson
- Isaac S. Kohane
- Yoshua Bengio
- Geoffrey E. Hinton
- Robert J. Carroll
- Abel N. Kho
- Quoc V. Le
- Trevor J. Hastie
- George Hripcsak
- Jerome H. Friedman
Who trusts Joshua Charles Denny overall
- Zexian Zeng
- Robert J. Carroll
- Wei-Qi Wei
- Yu Deng
- Jimeng Sun
- Alan R. Aronson
- Yuan Luo
- Yejin Kim
- Zhengping Che
- Yichen Wang
Papers from Joshua Charles Denny's perspective
Ordered by how strongly the researchers Joshua Charles Denny trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network. (2013) — 382 citations
- A gene-based association method for mapping traits using reference transcriptome data (2015) — 1,739 citations
- PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations (2010) — 1,141 citations
- Harnessing next-generation informatics for personalizing medicine: a report from AMIA's 2014 Health Policy Invitational Meeting (2016) — 7 citations
- Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data (2013) — 317 citations
- Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium (2011) — 351 citations
- Data from clinical notes: a perspective on the tension between structure and flexible documentation (2011) — 413 citations
- Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data (2013) — 986 citations
- Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies (2017) — 1,245 citations
- Research Paper: "Understanding" Medical School Curriculum Content Using KnowledgeMap (2003) — 127 citations
- A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries (2011) — 295 citations
- Extracting research-quality phenotypes from electronic health records to support precision medicine (2015) — 228 citations
- Importance of multi-modal approaches to effectively identify cataract cases from electronic health records (2012) — 124 citations
- STRATEGIES FOR EQUITABLE PHARMACOGENOMIC-GUIDED WARFARIN DOSING AMONG EUROPEAN AND AFRICAN AMERICAN INDIVIDUALS IN A CLINICAL POPULATION (2017) — 9 citations
- Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record (2015) — 73 citations
- Automated extraction of clinical traits of multiple sclerosis in electronic medical records (2013) — 59 citations
- Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics (2015) — 179 citations
- PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability (2016) — 347 citations
- The “All of Us” Research Program (2019) — 1,731 citations
- Artificial intelligence, bias and clinical safety (2019) — 796 citations