Seyed Mostafa Mousavi Kahaki

Biochemistry, Genetics and Molecular BiologyComputer ScienceEngineering

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: “Weakly supervised deep learning for predicting the response to hormonal treatment of women with atypical endometrial hyperplasia: a feasibility study”.

Weakly supervised deep learning for predicting the response to hormonal treatment of women with atypical endometrial hyperplasia: a feasibility study

PubMed(2023)10.1117/12.2652912

N/A

0DataRank · unranked

4 citations

Ian S. Hagemann, Kenny Cha, Christopher Trindade, Nicholas Petrick, Nicolas Kostelecky +2 more

End-to-end deep learning method for predicting hormonal treatment response in women with atypical endometrial hyperplasia or endometrial cancer

Journal of Medical Imaging(2024)10.1117/1.jmi.11.1.017502

N/A

0DataRank · unranked

3 citations

Ian S. Hagemann, Kenny H. Cha, Christopher Trindade, Nicholas Petrick, Nicolas Kostelecky +5 more