9 papers:
KDD-2015-CheKLBL- Deep Computational Phenotyping (ZC, DCK, WL, MTB, YL), pp. 507–516.
- KDD-2015-LiuWHX #framework #graph #health
- Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework (CL, FW, JH, HX), pp. 705–714.
- KDD-2014-HoGS #health #named
- Marble: high-throughput phenotyping from electronic health records via sparse nonnegative tensor factorization (JCH, JG, JS), pp. 115–124.
- KDD-2014-ZhouWHY #data-driven #metaprogramming
- From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records (JZ, FW, JH, JY), pp. 135–144.
- KDD-2013-SunBK #identification #optimisation #polynomial
- Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features (JS, JB, HRK), pp. 811–819.
KEOD-2012-ArnaudCSMNMSBJMM #modelling #ontology #towards- Towards a Reference Plant Trait Ontology for Modeling Knowledge of Plant Traits and Phenotypes (EA, LC, RS, NM, RTN, LM, MS, RB, PJ, LAM, GM), pp. 220–225.
MLDM-2011-PerezR #array #detection #using- Detection of Phenotypes in Microarray Data Using Force- Directed Placement Transformss (DVP, KAR), pp. 320–334.
CIKM-2003-TangZ #mining #multi- Mining multiple phenotype structures underlying gene expression profiles (CT, AZ), pp. 418–425.
- KDD-2003-TangZP #mining
- Mining phenotypes and informative genes from gene expression data (CT, AZ, JP), pp. 655–660.
