Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Alan D. Kaplan"'
Autor:
Kausar Abbas, Mintao Liu, Michael Wang, Duy Duong-Tran, Uttara Tipnis, Enrico Amico, Alan D. Kaplan, Mario Dzemidzic, David Kareken, Beau M. Ances, Jaroslaw Harezlak, Joaquín Goñi
Publikováno v:
iScience, Vol 26, Iss 9, Pp 107624- (2023)
Summary: Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent
Externí odkaz:
https://doaj.org/article/065fcd32b29f4483b3371d4d4db0fe72
Autor:
Duy Duong-Tran, Ralph Kaufmann, Jiong Chen, Xuan Wang, Sumita Garai, Frederick H. Xu, Jingxuan Bao, Enrico Amico, Alan D. Kaplan, Giovanni Petri, Joaquin Goni, Yize Zhao, Li Shen
Publikováno v:
Mathematics, Vol 12, Iss 3, p 455 (2024)
Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., a set of functional sub-circuits induced by node or edge attributes) and non-local (e.g., higher-order functional coordination patterns) proper
Externí odkaz:
https://doaj.org/article/25a914340ab04742adde15cef79ce56c
Autor:
Alan D. Kaplan, Uttara Tipnis, Jean C. Beckham, Nathan A. Kimbrel, David W. Oslin, Benjamin H. McMahon
Publikováno v:
Journal of biomedical informatics. 130
Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medicine. Difficulty in applying Machine Learning (ML) methods, either predictive or unsupervised, stems in part from the heterogeneity and irregular samp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d206acb86658ee4aef7a4c6b5b9e9832
https://pubmed.ncbi.nlm.nih.gov/35533991
https://pubmed.ncbi.nlm.nih.gov/35533991
Publikováno v:
Journal of Biomedical Informatics. 134:104163
We develop an unsupervised probabilistic model for heterogeneous Electronic Health Record (EHR) data. Utilizing a mixture model formulation, our approach directly models sequences of arbitrary length, such as medications and laboratory results. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::491619ff330a6b969b6fa01bae9a6ba0
https://doi.org/10.1016/j.jbi.2022.104163
https://doi.org/10.1016/j.jbi.2022.104163
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 12:479-488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b322758e036817e2a9990f71ead36d82
https://doi.org/10.1002/sam.11432
https://doi.org/10.1002/sam.11432
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 919:36-41
We present a novel trainable approach to distinguish neutrons from gammas using a particle detector . Traditionally, Pulse Shape Discrimination (PSD) methods for this problem utilize an ad-hoc computation of tail signal energy to perform the detectio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64735dae7149494d48d157bbeeec63e6
https://doi.org/10.1016/j.nima.2018.11.136
https://doi.org/10.1016/j.nima.2018.11.136
Autor:
Eric B. Duoss, Joshua K. Stolaroff, Du T. Nguyen, Congwang Ye, Albert Chu, William L. Smith, Aaron Wilson, Sachin S. Talathi, Brian Giera, Alan D. Kaplan
Publikováno v:
Lab on a Chip. 19:1808-1817
Microfluidic-based microencapsulation requires significant oversight to prevent material and quality loss due to sporadic disruptions in fluid flow that routinely arise. State-of-the-art microcapsule production is laborious and relies on experts to m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::038d99dc470770ff99016049ba007a92
https://doi.org/10.1039/c8lc01394b
https://doi.org/10.1039/c8lc01394b
Autor:
Luiz Pessoa, Kausar Abbas, Manasij Venkatesh, Alan D. Kaplan, Enrico Amico, Joaquín Goñi, Mario Ventresca, Mintao Liu, Jaroslaw Harezlak
Publikováno v:
Brain Connect
Background: Functional connectomes (FCs) have been shown to provide a reproducible individual fingerprint, which has opened the possibility of personalized medicine for neuro/psychiatric disorders. Thus, developing accurate ways to compare FCs is ess
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cdc293ce234d9c60ca076060282d463
http://arxiv.org/abs/2003.05393
http://arxiv.org/abs/2003.05393
Autor:
Kadri Aditya Mohan, Alan D. Kaplan
We present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural netw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::def7a0aee0286041edf17afa080cd588
Autor:
Harvey S. Levin, Adam R. Ferguson, Qi Cheng, Kadri Aditya Mohan, Shivshankar Sundaram, Joseph T. Giacino, Sonia Jain, Alan D. Kaplan, Austin Chou, Lindsay D. Nelson, Amy J. Markowitz, Abel Torres-Espín, Michael McCrea, Geoffrey T. Manley, J. Russell Huie
Publikováno v:
IEEE journal of biomedical and health informatics, vol 26, iss 3
IEEE J Biomed Health Inform
IEEE J Biomed Health Inform
Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators. This is due in part to the heterogeneity of damage inflicted to the brain, ultimately resulting in diverse and complex outcomes.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4c39fa26d86b6a9f205a6982d062b9d