🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Harry Subramanian

ORCID: 0000-0001-9173-6248

MedicineNeuroscienceBiochemistry, 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 6 papers. Top paper: “Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction”.

Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction

Frontiers in Neuroscience(2022)10.3389/fnins.2022.860208

N/A

0.529DataRank · unranked

33 citations

Khaled Bousabarah, Eve Kazarian, Tal Zeevi, Wolfgang Holler, Sara Merkaj +14 more

Trends in Development of Novel Machine Learning Methods for the Identification of Gliomas in Datasets That Include Non-Glioma Images: A Systematic Review

Frontiers in Oncology(2021)10.3389/fonc.2021.788819

N/A

0DataRank · unranked

13 citations

Rahul Dey, Waverly Rose Brim, Niklas Tillmanns, Gabriel Cassinelli Petersen, Alexandria Brackett +5 more

Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment

American Journal of Neuroradiology(2022)10.3174/ajnr.a7473

N/A

0DataRank · unranked

22 citations

Julia Shatalov, T. Verma, Waverly Rose Brim, Harry Subramanian, Alexandria Brackett +10 more

Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis

Frontiers in Oncology(2022)10.3389/fonc.2022.856231

N/A

0DataRank · unranked

18 citations

Sara Merkaj, Gabriel Cassinelli Petersen, Niklas Tillmanns, Harry Subramanian, Waverly Rose Brim +13 more

Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries

Neuro-Oncology Advances(2022)10.1093/noajnl/vdac093

N/A

0DataRank · unranked

7 citations

Avery E Lum, Gabriel Cassinelli, Sara Merkaj, T. Verma, Tal Zeevi +18 more

Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction

American Journal of Neuroradiology(2023)10.3174/ajnr.a8000

N/A

0DataRank · unranked

7 citations

Leon Jekel, Marc von Reppert, Niklas Tillmanns, Sara Merkaj, Gabriel Cassinelli Petersen +19 more