Sheng Yu - Citegraph

Author Info

Name	Affiliation	Papers
SHENG YU	Partners HealthCare Personalized Medicine, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, United States	19
Collaborators	Citations	PageRank
119	33	7.55
Referers	Referees	References
198	279	72

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100279

Publications (19 rows)

Collaborators (100 rows)

Referers (100 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
Biomedical Question Answering: A Survey of Approaches and Challenges	0	0.34	2023
CODER: Knowledge-infused cross-lingual medical term embedding for term normalization	1	0.37	2022
A Method for Generating Synthetic Electronic Medical Record Text	0	0.34	2021
Automated ICD coding via unsupervised knowledge integration (UNITE)	0	0.34	2020
Unsupervised multi-granular Chinese word segmentation and term discovery via graph partition	0	0.34	2020
Developing an automated mechanism to identify medical articles from wikipedia for knowledge extraction.	0	0.34	2020
Long-distance disorder-disorder relation extraction with bootstrapped noisy data	0	0.34	2020
f(1Feature Extraction for Phenotyping from Semantic and Knowledge Resources.	2	0.36	2019
High-throughput multimodal automated phenotyping (MAP) with application to PheWAS	0	0.34	2019
Long distance entity relation extraction with article structure embedding and applied to mining medical knowledge	0	0.34	2019
Enabling phenotypic big data with PheNorm.	2	0.38	2018
High-Throughput Multimodal Automated Phenotyping (MAP) Incorporating Natural Language Processing with Application to PheWAS.	0	0.34	2018
Generation of Synthetic Electronic Medical Record Text	1	0.36	2018
PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies.	1	0.35	2018
High-throughput Phenotyping via Denoised Normal Mixture Transformation.	0	0.34	2017
Surrogate-assisted feature extraction for high-throughput phenotyping.	2	0.37	2017
Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.	19	0.79	2015
Demonstrating the Advantages of Applying Data Mining Techniques on Time-Dependent Electronic Medical Records.	2	0.73	2015
Classification of CT pulmonary angiography reports by presence, chronicity, and location of pulmonary embolism with natural language processing.	3	0.45	2014

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