Peter Bjødstrup Jensen

Molecular Biology · 2011–2014

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 33 citations into it; #7,504 of 17,773 by trust here, #6,475 by citations
• Artificial Intelligence — 20 citations into it; #19,923 of 35,345 by trust here, #9,641 by citations

Whom Peter Bjødstrup Jensen trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alan R. Aronson
2. Tak-Chung Fu
3. Carol Friedman
4. Guergana K. Savova
5. Sharon I. Greenblum
6. Joshua Charles Denny
7. Stéphane M. Meystre
8. Isaac S. Kohane
9. Olivier Bodenreider
10. Lucila Ohno-Machado

Who trusts Peter Bjødstrup Jensen overall

1. Ying Sha
2. Jing Zhao
3. Phuoc Nguyen
4. Adnan Qayyum
5. Riccardo Miotto
6. Fei Wang
7. Robert Eriksson
8. Truyen Tran
9. May D. Wang
10. Aron Henriksson

Papers from Peter Bjødstrup Jensen's perspective

Ordered by how strongly the researchers Peter Bjødstrup Jensen trusts endorse each paper. Same corpus, a different order for every researcher.

1. A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries (Journal of Biomedical Informatics)
2. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program
3. Extracting Information from Textual Documents in the Electronic Health Record: A Review of Recent Research (Yearbook of Medical Informatics)
4. The eMERGE Network: A consortium of biorepositories linked to electronic medical records data for conducting genomic studies (BMC Medical Genomics)
5. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications
6. Automated encoding of clinical documents based on natural language processing. (JAMIA Journal of the American Medical Informatics Association)
7. Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium (Science Translational Medicine)
8. Electronic medical records for discovery research in rheumatoid arthritis
9. Electronic medical records for clinical research: application to the identification of heart failure.
10. HUMAN DISEASE

Their papers

• Mining electronic health records: towards better research applications and clinical care (2012) — 1,637 citations
• Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts (2011) — 309 citations
• Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients (2014) — 402 citations