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

Khaled Bousabarah

Sage Technologies (United States)

ORCID: 0009-0004-7699-9890
MedicineNeuroscience

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 3%percentile
1.5Author DataRank

Indexed papers

3in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 3 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information

Scientific Data(2024)10.1038/s41597-024-03021-9
Top 21%
0.980DataRank
Top 21%25 citations

Leon Jekel, Saahil Chadha, Anastasia Janas, Harrison Moy, Nazanin Maleki +17 more

Papers

Driven by 12 papers — median percentile 51. Top paper: “A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information”.

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information

Scientific Data(2024)10.1038/s41597-024-03021-9
Top 21%
0.980DataRank
Top 21%25 citations

Leon Jekel, Saahil Chadha, Anastasia Janas, Harrison Moy, Nazanin Maleki +17 more

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

The Journal of Machine Learning for Biomedical Imaging(2025)10.59275/j.melba.2025-9bd3
Top 49%
0.361DataRank
Top 49%7 citations

Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Rachit Saluja, Nader A. Fawzy +95 more

A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

arXiv (Cornell University)(2023)10.48550/arxiv.2309.05053
Top 65%
0.195DataRank
Top 65%2 citations

Leon Jekel, Saahil Chadha, Anastasia Janas, Harrison Moy, Nazanin Maleki +17 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

Comparison of volumetric and 2D-based response methods in the PNOC-001 pediatric low-grade glioma clinical trial

Neuro-Oncology Advances(2023)10.1093/noajnl/vdad172
N/A
0DataRank · unranked
9 citations

Divya Ramakrishnan, Sarah C. Brüningk, Fatima Memon, Sandra Abi Fadel, Nazanin Maleki +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

Comparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment ofBRAFV600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical Trial

American Journal of Neuroradiology(2024)10.3174/ajnr.a8189
N/A
0DataRank · unranked
5 citations

Sarah C. Brüningk, Marc von Reppert, Fatima Memon, Nazanin Maleki, Sanjay Aneja +10 more

Enhancing clinical decision-making: An externally validated machine learning model for predicting isocitrate dehydrogenase mutation in gliomas using radiomics from presurgical magnetic resonance imaging

Neuro-Oncology Advances(2024)10.1093/noajnl/vdae157
N/A
0DataRank · unranked
5 citations

Nader A. Fawzy, Leon Jekel, Marc von Reppert, Niklas Tillmanns, Klara Willms +13 more

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
0DataRank · unranked
33 citations

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

Noninvasive Tumor Profiling: Quantitative Contrast-enhanced MRI Markers Help Predict PD-L1 and CTNNB1 Status in Hepatocellular Carcinoma

Radiology(2025)10.1148/radiol.242750
N/A
0DataRank · unranked
7 citations

Rabea Sobirey, Margarita V. Revzin, Tal Zeevi, Moritz Gross, Victor Kasolowsky +15 more

Real-time PACS-integrated longitudinal brain metastasis tracking tool provides comprehensive assessment of treatment response to radiosurgery

Neuro-Oncology Advances(2022)10.1093/noajnl/vdac116
N/A
0DataRank · unranked
21 citations

Khaled Bousabarah, T. Verma, Marc von Reppert, Leon Jekel, Ayyüce Gordem +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