Zobrazeno 1 - 10
of 171
pro vyhledávání: '"Polosecki P"'
Autor:
Abrevaya, Germán, Ramezanian-Panahi, Mahta, Gagnon-Audet, Jean-Christophe, Polosecki, Pablo, Rish, Irina, Dawson, Silvina Ponce, Cecchi, Guillermo, Dumas, Guillaume
Scientific Machine Learning (SciML) is a burgeoning field that synergistically combines domain-aware and interpretable models with agnostic machine learning techniques. In this work, we introduce GOKU-UI, an evolution of the SciML generative model GO
Externí odkaz:
http://arxiv.org/abs/2307.05735
Autor:
Jenna M. Reinen, Pablo Polosecki, Eduardo Castro, Cheryl M. Corcoran, Guillermo A. Cecchi, Tiziano Colibazzi
Publikováno v:
Schizophrenia, Vol 10, Iss 1, Pp 1-8 (2024)
Abstract The prospective study of youths at clinical high risk (CHR) for psychosis, including neuroimaging, can identify neural signatures predictive of psychosis outcomes using algorithms that integrate complex information. Here, to identify risk an
Externí odkaz:
https://doaj.org/article/d95e77c82a74428fb10d4dafd35053c4
Autor:
Matias Aiskovich, Eduardo Castro, Jenna M. Reinen, Shreyas Fadnavis, Anushree Mehta, Hongyang Li, Amit Dhurandhar, Guillermo A. Cecchi, Pablo Polosecki
Publikováno v:
Frontiers in Radiology, Vol 4 (2024)
Data collection, curation, and cleaning constitute a crucial phase in Machine Learning (ML) projects. In biomedical ML, it is often desirable to leverage multiple datasets to increase sample size and diversity, but this poses unique challenges, which
Externí odkaz:
https://doaj.org/article/7c654a19c0fc43728e928fff94bba491
Autor:
Abrevaya, German, Rish, Irina, Aravkin, Aleksandr Y., Cecchi, Guillermo, Kozloski, James, Polosecki, Pablo, Zheng, Peng, Dawson, Silvina Ponce, Rhee, Juliana, Cox, David
Many real-world data sets, especially in biology, are produced by complex nonlinear dynamical systems. In this paper, we focus on brain calcium imaging (CaI) of different organisms (zebrafish and rat), aiming to build a model of joint activation dyna
Externí odkaz:
http://arxiv.org/abs/1805.09874
Akademický článek
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Baseline multimodal information predicts future motor impairment in premanifest Huntington's disease
Autor:
Eduardo Castro, Pablo Polosecki, Irina Rish, Dorian Pustina, John H. Warner, Andrew Wood, Cristina Sampaio, Guillermo A. Cecchi
Publikováno v:
NeuroImage: Clinical, Vol 19, Iss , Pp 443-453 (2018)
In Huntington's disease (HD), accurate estimates of expected future motor impairments are key for clinical trials. Individual prognosis is only partially explained by genetics. However, studies so far have focused on predicting the time to clinical d
Externí odkaz:
https://doaj.org/article/909389c205d04a9b9f58108aa89c616f
Autor:
Aiskovich M; SilverGate Team, IBM Argentina, Buenos Aires, Argentina., Castro E; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Reinen JM; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Fadnavis S; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Mehta A; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Li H; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Dhurandhar A; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Cecchi GA; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States., Polosecki P; IBM T. J. Watson Research Center, Yorktown Heights, New York, NY, United States.
Publikováno v:
Frontiers in radiology [Front Radiol] 2024 Apr 05; Vol. 4, pp. 1283392. Date of Electronic Publication: 2024 Apr 05 (Print Publication: 2024).
Autor:
Mina Gheiratmand, Irina Rish, Guillermo A. Cecchi, Matthew R. G. Brown, Russell Greiner, Pablo I. Polosecki, Pouya Bashivan, Andrew J. Greenshaw, Rajamannar Ramasubbu, Serdar M. Dursun
Publikováno v:
npj Schizophrenia, Vol 3, Iss 1, Pp 1-12 (2017)
Neuroimaging: Brain connectivity pattern predicts symptom severity Brain network analyses from functional magnetic resonance imaging (fMRI) data may help diagnose schizophrenia and predict symptom severity. Detecting neuroimaging patterns requires la
Externí odkaz:
https://doaj.org/article/c2d7e64345e8436c975666a48119346f
Akademický článek
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