Fateme Nateghi Haredasht

Also affiliated with Stanford Medicine, Stanford University

Computer ScienceMedicineBiochemistry, Genetics and Molecular Biology

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 4 papers. Top paper: “Clinical entity augmented retrieval for clinical information extraction”.

Clinical entity augmented retrieval for clinical information extraction

npj Digital Medicine(2025)10.1038/s41746-024-01377-1

N/A

0.601DataRank · unranked

54 citations

Akshay Swaminathan, Karthik S. Vedula, Sanjana Narayanan, Fateme Nateghi Haredasht, P. Stephen +7 more

First, do NOHARM: a medical safety benchmark and randomized study of physician and AI teaming on clinical consultations

arXiv (Cornell University)(2025)10.48550/arxiv.2512.01241

N/A

0.335DataRank · unranked

5 citations

Fateme Nateghi Haredasht, Saloni Kumar Maharaj, Jain, Priyank, Jessica Tran, Matthew Gwiazdon +46 more

Predictability of buprenorphine‐naloxone treatment retention: A multi‐site analysis combining electronic health records and machine learning

Addiction(2024)10.1111/add.16587

N/A

0DataRank · unranked

6 citations

Sajjad Fouladvand, Steven Tate, Min Min Chan, Joannas Jie Lin Yeow, Kira Griffiths +11 more

Predicting treatment retention in medication for opioid use disorder: a machine learning approach using NLP and LLM-derived clinical features

Journal of the American Medical Informatics Association(2025)10.1093/jamia/ocaf157

N/A

0DataRank · unranked

4 citations

Iván López, Steven Tate, Pooya Ashtari, Min Min Chan, Deepali Kulkarni +11 more