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

Fostering Data Sharing

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Albert Montillo

Albert Montillo

Southwestern Medical Center

ORCID: 0000-0002-4353-290X

Also affiliated with Southwestern Medical Center, Southwestern University, The University of Texas Southwestern Medical Center

NeuroscienceComputer ScienceMedicine

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 4%percentile

0.668Author DataRank

Indexed papers

1in 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 1 indexed paper 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.

Glaucoma Diagnosis Through the Integration of Optical Coherence Tomography/Angiography and Machine Learning Diagnostic Models

Clinical ophthalmology(2022)10.2147/opth.s367722

Top 30%

0.668DataRank

Top 30%13 citations

Ashika Angirekula, Alex Treacher, Ghadeer Al-Humimat, Mohamed F. Marzban, Alyssa Chen +7 more

Papers

Driven by 13 papers — median percentile 70. Top paper: “Whole Brain Segmentation”.

Whole Brain Segmentation

Neuron(2002)10.1016/s0896-6273(02)00569-x

N/A

1.4DataRank · unranked

8963 citations

David H. Salat, Evelina Busa, Marilyn Albert, Megan Dieterich, Christian Haselgrove +12 more

Glaucoma Diagnosis Through the Integration of Optical Coherence Tomography/Angiography and Machine Learning Diagnostic Models

Clinical ophthalmology(2022)10.2147/opth.s367722

Top 30%

0.668DataRank

Top 30%13 citations

Ashika Angirekula, Alex Treacher, Ghadeer Al-Humimat, Mohamed F. Marzban, Alyssa Chen +7 more

Patterns of Pretreatment Reward Task Brain Activation Predict Individual Antidepressant Response: Key Results From the EMBARC Randomized Clinical Trial

Biological Psychiatry(2021)10.1016/j.biopsych.2021.09.011

N/A

0DataRank · unranked

26 citations

Cherise Chin Fatt, Alex Treacher, Cooper Mellema, Crystal Cooper, Manish K. Jha +8 more

Pitfalls and recommended strategies and metrics for suppressing motion artifacts in functional MRI

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.09.18.460908

N/A

0DataRank · unranked

0 citations

Kevin P. Nguyen, Marco C. Pinho, Richard B. Dewey, Madhukar H. Trivedi, Albert Montillo +1 more

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning

Scientific Reports(2022)10.1038/s41598-022-06459-2

N/A

0DataRank · unranked

56 citations

Kevin P. Nguyen, Alex Treacher, Albert Montillo, Cooper Mellema

Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder

Nature Communications(2022)10.1038/s41467-022-31053-5

N/A

0DataRank · unranked

46 citations

Alex Treacher, Emre Caglayan, Danni Luo, Jillian R. Haney, Michael J. Gandal +4 more

Predictive Patterns of Antidepressant Response from Pre-Treatment Reward Processing using Functional MRI and Deep Learning: Key Results from the EMBARC Randomized Clinical Trial

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.01.28.923821

N/A

0DataRank · unranked

1 citations

Cherise Chin Fatt, Alex Treacher, Cooper Mellema, Crystal Cooper, Manish K. Jha +8 more

BLENDS: Augmentation of Functional Magnetic Resonance Images for Machine Learning Using Anatomically Constrained Warping

Brain Connectivity(2022)10.1089/brain.2021.0186

N/A

0DataRank · unranked

3 citations

Vyom Raval, Abu Minhajuddin, Thomas Carmody, Madhukar H. Trivedi, Richard B. Dewey +2 more

Adversarially-Regularized Mixed Effects Deep Learning (ARMED) Models Improve Interpretability, Performance, and Generalization on Clustered (non-iid) Data

IEEE Transactions on Pattern Analysis and Machine Intelligence(2023)10.1109/tpami.2023.3234291

N/A

0DataRank · unranked

8 citations

Alex Treacher, Albert Montillo, Kevin P. Nguyen

Novel machine learning approaches for improving the reproducibility and reliability of functional and effective connectivity from functional MRI

Journal of Neural Engineering(2023)10.1088/1741-2552/ad0c5f

N/A

0DataRank · unranked

3 citations

Albert Montillo, Cooper Mellema

Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data

arXiv (Cornell University)(2023)10.48550/arxiv.2310.03146

N/A

0DataRank · unranked

0 citations

Adam Wang, Albert Montillo, Son Hoang Nguyen

Machine Learning Prediction of Lymph Node Metastasis in Breast Cancer: Performance of a Multi-institutional MRI-based 4D Convolutional Neural Network

Radiology Imaging Cancer(2024)10.1148/rycan.230107

N/A

0DataRank · unranked

8 citations

Son Hoang Nguyen, Paniz Karbasi, Keith Hulsey, Murat Can Çobanoğlu, Liqiang Wang +3 more

Longitudinal prognosis of Parkinson’s outcomes using causal connectivity

NeuroImage Clinical(2024)10.1016/j.nicl.2024.103571

N/A

0DataRank · unranked

3 citations

Kevin P. Nguyen, Alex Treacher, Aixa X. Andrade, Nader Pouratian, Vibhash D. Sharma +3 more