The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies JV van Vliet-Ostaptchouk, ML Nuotio, SN Slagter, D Doiron, K Fischer, ... BMC endocrine disorders 14, 1-13, 2014 | 791 | 2014 |
CLO: the cell line ontology S Sarntivijai, Y Lin, Z Xiang, TF Meehan, AD Diehl, UD Vempati, ... Journal of biomedical semantics 5, 1-10, 2014 | 132 | 2014 |
MOLGENIS research: advanced bioinformatics data software for non-bioinformaticians KJ van der Velde, F Imhann, B Charbon, C Pang, D van Enckevort, ... Bioinformatics 35 (6), 1076-1078, 2019 | 88 | 2019 |
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks C Pang, X Jiang, KS Kalluri, M Spotnitz, RJ Chen, A Perotte, K Natarajan Machine Learning for Health, 239-260, 2021 | 58 | 2021 |
SORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data C Pang, A Sollie, A Sijtsma, D Hendriksen, B Charbon, M de Haan, ... Database 2015, bav089, 2015 | 49 | 2015 |
BiobankConnect: software to rapidly connect data elements for pooled analysis across biobanks using ontological and lexical indexing C Pang, D Hendriksen, M Dijkstra, KJ van der Velde, J Kuiper, HL Hillege, ... Journal of the American Medical Informatics Association 22 (1), 65-75, 2015 | 41 | 2015 |
Development and validation of prediction models for mechanical ventilation, renal replacement therapy, and readmission in COVID-19 patients VA Rodriguez, S Bhave, R Chen, C Pang, G Hripcsak, S Sengupta, ... Journal of the American Medical Informatics Association 28 (7), 1480-1488, 2021 | 30 | 2021 |
Observ‐OM and Observ‐TAB: Universal syntax solutions for the integration, search, and exchange of phenotype and genotype information T Adamusiak, H Parkinson, J Muilu, E Roos, KJ van der Velde, ... Human mutation 33 (5), 867-873, 2012 | 29 | 2012 |
Cell Line Ontology: Redesigning the Cell Line Knowledgebase to Aid Integrative Translational Informatics. S Sarntivijai, Z Xiang, TF Meehan, AD Diehl, U Vempati, SC Schürer, ... ICBO 833, 25-32, 2011 | 22 | 2011 |
MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks C Pang, D van Enckevort, M de Haan, F Kelpin, J Jetten, D Hendriksen, ... Bioinformatics 32 (14), 2176-2183, 2016 | 17 | 2016 |
Comparative effectiveness of medical concept embedding for feature engineering in phenotyping J Lee, C Liu, JH Kim, A Butler, N Shang, C Pang, K Natarajan, P Ryan, ... JAMIA open 4 (2), ooab028, 2021 | 11 | 2021 |
The Vertebrate Bridging Ontology (VBO). RS Travillian, J Malone, C Pang, JM Hancock, PWH Holland, ... ICBO, 2011 | 9 | 2011 |
BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration C Pang, F Kelpin, D van Enckevort, N Eklund, K Silander, D Hendriksen, ... Bioinformatics 33 (22), 3627-3634, 2017 | 6 | 2017 |
CEHR-GPT: Generating electronic health records with chronological patient timelines C Pang, X Jiang, NP Pavinkurve, KS Kalluri, EL Minto, J Patterson, ... arXiv preprint arXiv:2402.04400, 2024 | 3 | 2024 |
Phenotype concept set construction from concept pair likelihoods VA Rodriguez, S Tony, P Thangaraj, C Pang, KS Kalluri, X Jiang, ... AMIA Annual Symposium Proceedings 2020, 1080, 2021 | 3 | 2021 |
Comparative effectiveness of knowledge graphs-and EHR data-based medical concept embedding for phenotyping J Lee, C Liu, JH Kim, A Butler, N Shang, C Pang, K Natarajan, P Ryan, ... medRxiv, 2020 | 1 | 2020 |
MOLGENIS catalogue M Swertz, D van Enckevort, C Pang Journal of Clinical Bioinformatics 5 (Suppl 1), S8, 2015 | 1 | 2015 |
Rapid Development of an Ontology of Coriell Cell Lines. C Pang, T Adamusiak, HE Parkinson, J Malone ICBO, 2011 | 1 | 2011 |
The Coriell Cell Line Ontology: Rapidly Developing Large Ontologies C Pang, T Adamusiak, H Parkinson, J Malone Bio-Ontologies 2011, 2011 | 1 | 2011 |
joerivandervelde/molgenis: MOLGENIS v1. 21.2 G1 D Hendriksen, M de Haan, B Charbon, C Pang, F Kelpin, R Kanninga, ... | | 2016 |