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ORCIDBrian Caffo
Brian S. Caffo – Brian C. Caffo
Person information
- affiliation: Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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2020 – today
- 2024
[c10]Ruxiao Duan, Brian Caffo, Harrison X. Bai, Haris I. Sair, Craig K. Jones:
Evidential Uncertainty Quantification: A Variance-Based Perspective. WACV 2024: 2121-2130- 2023
- [j37]Brian S. Caffo, Fabio Aurelio D'Asaro, Artur Garcez, Emanuela Raffinetti:
Corrigendum: Editorial: Explainable artificial intelligence models and methods in finance and healthcare. Frontiers Artif. Intell. 6 (2023) - [j36]Itzy E. Morales Pantoja
, Lena Smirnova, Alysson R. Muotri, Karl J. Wahlin, Jeffrey Kahn, J. Lomax Boyd, David H. Gracias, Timothy D. Harris, Tzahi Cohen-Karni, Brian S. Caffo, Alexander S. Szalay, Fang Han, Donald J. Zack, Ralph Etienne-Cummings, Akwasi Akwaboah, July Carolina Romero, Dowlette-Mary Alam El Din, Jesse D. Plotkin, Barton L. Paulhamus, Erik C. Johnson, Frederic Gilbert, J. Lowry Curley, Ben Cappiello, Jens C. Schwamborn, Eric J. Hill, Paul Roach, Daniel Tornero, Caroline Krall, Rheinallt Parri, Fenna Sillé, Andre Levchenko, Rabih E. Jabbour, Brett J. Kagan, Cynthia A. Berlinicke, Qi Huang, Alexandra Maertens, Kathrin Herrmann, Katya Tsaioun, Raha M. Dastgheyb, Christa Whelan Habela, Joshua T. Vogelstein, Thomas Hartung:
First Organoid Intelligence (OI) workshop to form an OI community. Frontiers Artif. Intell. 6 (2023) - [j35]Amanda F. Mejia, David Bolin, Yu Ryan Yue, Jiongran Wang, Brian S. Caffo, Mary Beth Nebel:
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference. J. Comput. Graph. Stat. 32(2): 413-433 (2023) - [j34]Tanmay Nath, Brian Caffo, Tor D. Wager, Martin A. Lindquist:
A machine learning based approach towards high-dimensional mediation analysis. NeuroImage 268: 119843 (2023) - [c9]Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein:
Prospective Learning: Principled Extrapolation to the Future. CoLLAs 2023: 347-357 - [i7]Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, Joshua T. Vogelstein:
Learning sources of variability from high-dimensional observational studies. CoRR abs/2307.13868 (2023) - [i6]Sohaib Naim, Brian Caffo, Haris I. Sair, Craig K. Jones:
Applications of Sequential Learning for Medical Image Classification. CoRR abs/2309.14591 (2023) - [i5]Babak Moghadas, Brian S. Caffo:
Empowering Learning: Standalone, Browser-Only Courses for Seamless Education. CoRR abs/2311.06961 (2023) - [i4]Ruxiao Duan, Brian Caffo, Harrison X. Bai, Haris I. Sair, Craig K. Jones:
Evidential Uncertainty Quantification: A Variance-Based Perspective. CoRR abs/2311.11367 (2023) - 2022
- [j33]Brian S. Caffo, Fabio Aurelio D'Asaro, Artur Garcez, Emanuela Raffinetti:
Editorial: Explainable artificial intelligence models and methods in finance and healthcare. Frontiers Artif. Intell. 5 (2022) - [j32]Bohua Wan, Brian Caffo, S. Swaroop Vedula:
A Unified Framework on Generalizability of Clinical Prediction Models. Frontiers Artif. Intell. 5: 872720 (2022) - [i3]Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang:
Prospective Learning: Back to the Future. CoRR abs/2201.07372 (2022) - [i2]Jacob Renn, Ian Sotnek, Benjamin Harvey, Brian Caffo:
The Multiple Subnetwork Hypothesis: Enabling Multidomain Learning by Isolating Task-Specific Subnetworks in Feedforward Neural Networks. CoRR abs/2207.08821 (2022) - 2021
- [j31]Eric W. Bridgeford, Shangsi Wang, Zeyi Wang, Ting Xu, R. Cameron Craddock, Jayanta Dey, Gregory Kiar, William R. Gray Roncal, Carlo Colantuoni, Christopher Douville, Stephanie Noble, Carey E. Priebe, Brian Caffo, Michael P. Milham, Xi-Nian Zuo, Joshua T. Vogelstein:
Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics. PLoS Comput. Biol. 17(9) (2021) - 2020
- [j30]Yi Zhao, Martin A. Lindquist, Brian S. Caffo:
Sparse principal component based high-dimensional mediation analysis. Comput. Stat. Data Anal. 142 (2020) - [j29]Tingting Zhang, Yinge Sun, Huazhang Li, Guofen Yan, Seiji Tanabe, Ruizhong Miao, Yaotian Wang, Brian S. Caffo, Mark S. Quigg:
Bayesian inference of a directional brain network model for intracranial EEG data. Comput. Stat. Data Anal. 144: 106847 (2020) - [j28]Adrian Gherman, John Muschelli, Brian Caffo, Ciprian M. Crainiceanu:
Rxnat: An Open-Source R Package for XNAT-Based Repositories. Frontiers Neuroinformatics 14: 572068 (2020) - [c8]Tharindu De Silva, S. Swaroop Vedula, Alexander Perdomo-Pantoja, Rohan Vijayan, Sophia A. Doerr, Ali Uneri, Runze Han, Michael D. Ketcha, R. L. Skolasky Jr., Brian Caffo, Greg Hager, Timothy Witham, Nicholas Theodore, Jeffrey H. Siewerdsen:
SpineCloud: image analytics for predictive modeling of spine surgery outcomes. Medical Imaging: Image-Guided Procedures 2020: 113151O
2010 – 2019
- 2019
- [j27]Che Ngufor, Holly Van Houten, Brian S. Caffo, Nilay D. Shah, Rozalina G. McCoy:
Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c. J. Biomed. Informatics 89: 56-67 (2019) - [j26]Heather Shappell, Brian S. Caffo, James J. Pekar, Martin A. Lindquist:
Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. NeuroImage 191: 243-257 (2019) - 2018
- [j25]Amanda F. Mejia, Mary Beth Nebel, Anita D. Barber, Ann S. Choe, James J. Pekar, Brian S. Caffo, Martin A. Lindquist:
Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. NeuroImage 172: 478-491 (2018) - 2017
- [j24]Maleeha F. Syed, Martin A. Lindquist, Jay J. Pillai, Shruti Agarwal, Sachin K. Gujar, Ann S. Choe, Brian Caffo, Haris I. Sair:
Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging. Brain Connect. 7(10): 635-642 (2017) - [j23]Ann S. Choe, Mary Beth Nebel, Anita D. Barber, Jessica R. Cohen, Yuting Xu, James J. Pekar, Brian Caffo, Martin A. Lindquist:
Comparing test-retest reliability of dynamic functional connectivity methods. NeuroImage 158: 155-175 (2017) - [j22]Shaojie Chen, Kai Liu, Yuguang Yang, Yuting Xu, Seonjoo Lee, Martin A. Lindquist, Brian S. Caffo, Joshua T. Vogelstein:
An M-estimator for reduced-rank system identification. Pattern Recognit. Lett. 86: 76-81 (2017) - 2016
- [j21]Robert E. Kass, Brian S. Caffo, Marie Davidian, Xiao-Li Meng, Bin Yu, Nancy Reid:
Ten Simple Rules for Effective Statistical Practice. PLoS Comput. Biol. 12(6) (2016) - 2015
- [j20]Chen Yue, Shaojie Chen, Haris I. Sair, Raag D. Airan, Brian S. Caffo:
Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models. Comput. Stat. Data Anal. 89: 126-133 (2015) - [j19]Amanda F. Mejia, Mary Beth Nebel, Haochang Shou, Ciprian M. Crainiceanu, James J. Pekar, Stewart H. Mostofsky, Brian Caffo, Martin A. Lindquist:
Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators. NeuroImage 112: 14-29 (2015) - [c7]Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo:
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes. ICML 2015: 1843-1851 - [c6]Huitong Qiu, Fang Han, Han Liu, Brian Caffo:
Robust Portfolio Optimization. NIPS 2015: 46-54 - 2014
- [j18]John Muschelli, Mary Beth Nebel, Brian S. Caffo, Anita D. Barber, James J. Pekar, Stewart H. Mostofsky:
Reduction of motion-related artifacts in resting state fMRI using aCompCor. NeuroImage 96: 22-35 (2014) - [j17]Martin A. Lindquist, Yuting Xu, Mary Beth Nebel, Brian S. Caffo:
Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. NeuroImage 101: 531-546 (2014) - [j16]Haochang Shou, Ani Eloyan, Mary Beth Nebel, Amanda F. Mejia, James J. Pekar, Stewart H. Mostofsky, Brian S. Caffo, Martin A. Lindquist, Ciprian M. Crainiceanu:
Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI. NeuroImage 102: 938-944 (2014) - [i1]Gagan Sidhu, Brian Caffo:
MONEYBaRL: Exploiting pitcher decision-making using Reinforcement Learning. CoRR abs/1407.8392 (2014) - 2013
- [j15]Anita D. Barber, Brian S. Caffo, James J. Pekar, Stewart H. Mostofsky:
Effects of Working Memory Demand on Neural Mechanisms of Motor Response Selection and Control. J. Cogn. Neurosci. 25(8): 1235-1248 (2013) - [j14]Martin A. Lindquist, Brian C. Caffo, Ciprian M. Crainiceanu:
Ironing out the statistical wrinkles in "ten ironic rules". NeuroImage 81: 499-502 (2013) - [c5]Seonjoo Lee, Vadim Zipunnikov, Navid Shiee, Ciprian M. Crainiceanu, Brian S. Caffo, Dzung L. Pham:
Clustering of High Dimensional Longitudinal Imaging Data. PRNI 2013: 33-36 - [c4]Russell T. Shinohara, Ciprian S. Crainiceanu, Brian S. Caffo, Daniel S. Reich:
Information Criteria for Dynamic Contrast-Enhanced Magnetic Resonance Imaging. PRNI 2013: 37-41 - 2012
- [j13]Xue Yang, Carolyn B. Lauzon, Ciprian M. Crainiceanu, Brian C. Caffo, Susan M. Resnick, Bennett A. Landman:
Biological parametric mapping accounting for random regressors with regression calibration and model II regression. NeuroImage 62(3): 1761-1768 (2012) - [j12]Bruno M. Jedynak, Andrew Lang, Bo Liu, Elyse Katz, Yanwei Zhang, Bradley T. Wyman, David Raunig, C. Pierre Jedynak, Brian Caffo, Jerry L. Prince:
A computational neurodegenerative disease progression score: Method and results with the Alzheimer's disease neuroimaging initiative cohort. NeuroImage 63(3): 1478-1486 (2012) - [c3]Carolyn B. Lauzon, Brian C. Caffo, Bennett A. Landman:
Towards automatic quantitative quality control for MRI. Medical Imaging: Image Processing 2012: 83140K - 2011
- [j11]Jeff Goldsmith, Ciprian M. Crainiceanu, Brian S. Caffo, Daniel S. Reich:
Penalized functional regression analysis of white-matter tract profiles in multiple sclerosis. NeuroImage 57(2): 431-439 (2011) - [j10]Russell T. Shinohara, Ciprian M. Crainiceanu, Brian S. Caffo, María Inés Gaitán, Daniel S. Reich:
Population-wide principal component-based quantification of blood-brain-barrier dynamics in multiple sclerosis. NeuroImage 57(4): 1430-1446 (2011) - [j9]Vadim Zipunnikov, Brian C. Caffo, David M. Yousem, Christos Davatzikos, Brian S. Schwartz, Ciprian M. Crainiceanu:
Functional principal component model for high-dimensional brain imaging. NeuroImage 58(3): 772-784 (2011) - [c2]Xue Yang, Carolyn B. Lauzon, Ciprian M. Crainiceanu, Brian C. Caffo, Susan M. Resnick, Bennett A. Landman:
Accounting for Random Regressors: A Unified Approach to Multi-modality Imaging. MBIA 2011: 1-9 - [c1]Carolyn B. Lauzon, Andrew J. Asman, Ciprian M. Crainiceanu, Brian C. Caffo, Bennett A. Landman:
Assessment of Bias for MRI Diffusion Tensor Imaging Using SIMEX. MICCAI (2) 2011: 107-115 - 2010
- [j8]Dana Frances Boatman-Reich, Piotr J. Franaszczuk, Anna Korzeniewska, Brian Caffo, Eva K. Ritzl, Sarah Colwell, Nathan E. Crone:
Quantifying auditory event-related responses in multichannel human intracranial recordings. Frontiers Comput. Neurosci. 4: 4 (2010) - [j7]Brian S. Caffo, Ciprian M. Crainiceanu, Guillermo Verduzco, Suresh Joel, Stewart H. Mostofsky, Susan Spear Bassett, James J. Pekar:
Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk. NeuroImage 51(3): 1140-1149 (2010)
2000 – 2009
- 2008
- [j6]F. DuBois Bowman, Brian Caffo, Susan Spear Bassett, Clint Kilts:
A Bayesian hierarchical framework for spatial modeling of fMRI data. NeuroImage 39(1): 146-156 (2008) - [j5]Xin He, Brian S. Caffo, Eric C. Frey:
Toward Realistic and Practical Ideal Observer (IO) Estimation for the Optimization of Medical Imaging Systems. IEEE Trans. Medical Imaging 27(10): 1535-1543 (2008) - 2007
- [j4]Brian C. Caffo, Ming-Wen An, Charles Rohde:
Flexible random intercept models for binary outcomes using mixtures of normals. Comput. Stat. Data Anal. 51(11): 5220-5235 (2007) - [j3]Brian S. Schwartz, Sining Chen, Brian Caffo, Walter F. Stewart, Karen I. Bolla, David M. Yousem, Christos Davatzikos:
Relations of brain volumes with cognitive function in males 45 years and older with past lead exposure. NeuroImage 37(2): 633-641 (2007) - [j2]Leena Choi, Brian C. Caffo, Charles Rohde:
Optimal sampling times in bioequivalence studies using a simulated annealing algorithm. Stat. Comput. 17(4): 337-347 (2007) - 2004
- [j1]Alan Agresti, Brian C. Caffo, Pamela Ohman-Strickland:
Examples in which misspecification of a random effects distribution reduces efficiency, and possible remedies. Comput. Stat. Data Anal. 47(3): 639-653 (2004)
Coauthor Index
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last updated on 2024-10-09 20:32 CEST by the dblp team
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