Jonathan Moran Sierra

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 2 papers. Top paper: “Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo, Flan-T5 and spaCy’s Rule-based & Machine Learning-based methods”.

Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo, Flan-T5 and spaCy’s Rule-based & Machine Learning-based methods

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.09.27.559788

N/A

0DataRank · unranked

8 citations

Inez Y. Oh, Jonathan Moran Sierra, Jonathan Tang, Philip Payne, Zachary B. Abrams +2 more

Leveraging GPT-4 for identifying cancer phenotypes in electronic health records: a performance comparison between GPT-4, GPT-3.5-turbo, Flan-T5, Llama-3-8B, and spaCy’s rule-based and machine learning-based methods

JAMIA Open(2024)10.1093/jamiaopen/ooae060

N/A

0DataRank · unranked

42 citations

Inez Y. Oh, Jonathan Moran Sierra, Jonathan Tang, Philip Payne, Zach Abrams +2 more