Author

S. M. Resnick

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 4 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 4 Organism:human· 3 Assay:imaging· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Research Focus:gene regulatory network inference· 2 Research Focus:cell-cell communication· 1

Frequent Co-Authors

A. Abdulkadir· 2 shared A. T. Shafer· 2 shared B. A. Landman· 2 shared D. Srinivasan· 2 shared E. Mamourian· 2 shared G. Erus· 2 shared I. Nasrallah· 2 shared J. Wen· 2 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersBioengineering

A. Abdulkadir

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Author profile →

5 papers

Recent·Most cited

Genetic, Clinical Underpinnings of Brain Change Along Two Neuroanatomical Dimensions of Clinically-defined Alzheimer's Disease

J. Wen, Z. Yang, I. Nasrallah, Y. Cui, G. Erus, D. Srinivasan, A. Abdulkadir, E. Mamourian, I. Skampardoni, G. Hwang, A. Singh, M. Bergman, J. Bao, E. Varol, Z. Zhou, , Sh

This study identifies two brain atrophy dimensions in Alzheimer's disease using Surreal-GAN and links them to genetic and clinical factors, revealing distinct pathological mechanisms.

bioRxiv · Sep 16, 2022 · PreprintBioengineering

Multiscale functional connectivity patterns of the aging brain learned from rsfMRI data of 4,259 individuals of the multi-cohort iSTAGING study

Z. Zhou, D. Srinivasan, H. Li, A. Abdulkadir, I. Nasrallah, J. Wen, J. Doshi, G. Erus, E. Mamourian, N. R. Bryan, D. A. Wolk, L. Beason-Held, S. M. Resnick, T. D. Satterthwaite, C. Davatzikos, , Y. Fan

The paper develops a brain age prediction model using multiscale functional connectivity from rsfMRI data of 4,259 individuals, showing that multiscale measures improve prediction and that brain age gaps correlate with cognitive and clinical measures.

bioRxiv · Jul 27, 2022 · PreprintBioengineering

PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images

L. Y. Cai, Q. Yang, C. B. Hansen, V. Nath, K. Ramadass, G. W. Johnson, B. N. Conrad, B. D. Boyd, J. P. Begnoche, L. L. Beason-Held, A. T. Shafer, S. M. Resnick, W. D. Taylor, G. R. Price, V. L. Morgan, , B. A. Landman

The paper introduces PreQual, an automated pipeline that preprocesses and quality assures diffusion weighted MRI images using multiple tools and generates QA reports.

bioRxiv · Sep 14, 2020Bioengineering

Distortion correction of diffusion weighted MRI without reverse phase-encoding scans or field-maps

K. G. Schilling, J. Blaber, C. Hansen, L. Cai, B. Rogers, A. W. Anderson, S. Smith, P. Kanakaraj, T. Rex, S. M. Resnick, A. T. Shafer, L. Cutting, N. Woodward, D. Zald, B. A. Landman

This study develops a deep learning method to correct diffusion MRI distortions without reverse phase-encoding scans or field maps, showing effective correction on diverse datasets.

bioRxiv · Jan 19, 2020 · PreprintBioengineering

Discovery of several thousand highly diverse circular DNA viruses

M. J. Tisza, D. V. Pastrana, N. L. Welch, B. Stewart, A. Peretti, G. J. Starrett, Y.-Y. S. Pang, S. R. Krishnamurthy, P. A. Pesavento, D. H. McDermott, P. M. Murphy, J. L. Whited, B. Miller, J. M. Brenchley, S. P. Rosshart, , C. B. Buck

The paper identifies and characterizes thousands of new circular DNA viruses from animal samples using a bioinformatics pipeline and artificial neural networks.

bioRxiv · Sep 17, 2019Microbiology