Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery

Autor: Nicolas Traut, Katja Heuer, Guillaume Lemaître, Anita Beggiato, David Germanaud, Monique Elmaleh, Alban Bethegnies, Laurent Bonnasse-Gahot, Weidong Cai, Stanislas Chambon, Freddy Cliquet, Ayoub Ghriss, Nicolas Guigui, Amicie de Pierrefeu, Meng Wang, Valentina Zantedeschi, Alexandre Boucaud, Joris van den Bossche, Balázs Kegl, Richard Delorme, Thomas Bourgeron, Roberto Toro, Gaël Varoquaux

Publikováno v: NeuroImage, Vol 255, Iss , Pp 119171- (2022)

MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, und

Externí odkaz: https://doaj.org/article/1fea146ac4c34cb3954bdb6784be4e75

Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery

Autor: Monique Elmaleh, Freddy Cliquet, Nicolas Guigui, David Germanaud, Ayoub Ghriss, Balázs Kégl, Anita Beggiato, Roberto Toro, Richard Delorme, Amicie de Pierrefeu, Valentina Zantedeschi, Joris Van den Bossche, Nicolas Traut, Laurent Bonasse-Gahot, Alexandre Boucaud, Alban Bethegies, Guillaume Lemaitre, Thomas Bourgeron, Katja Heuer, Meng Wang, Gael Varauquaux, Weidong Cai, Stanislas Chambon

Publikováno v: NeuroImage
NeuroImage, Elsevier, 2022, 255, pp.119171. ⟨10.1016/j.neuroimage.2022.119171⟩
NeuroImage, 2022, 255, pp.119171. ⟨10.1016/j.neuroimage.2022.119171⟩

MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, und

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16f2cfae0d811c5bca38d72bf01cd1a0
https://hdl.handle.net/21.11116/0000-000A-51C0-121.11116/0000-000A-51BE-5

Diagnosis of congenital pigmented macules in infants with reflectance confocal microscopy and machine learning

Autor: Brigitte Dréno, Philippe Bahadoran, Morgane Vourc'h, Sébastien Barbarot, Kevin Roussel, Anouk Soenen, Jilliana Monnier, Azzam Alkhalifah, Stanislas Chambon, Brigitte Keriven Dessomme, Christine Chiaverini, Sébastien Debarbieux

Publikováno v: Journal of The American Academy of Dermatology
Journal of The American Academy of Dermatology, 2021, 85 (5), pp.1308-1309. ⟨10.1016/j.jaad.2020.09.025⟩

International audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8183c89972fe2f7c6f5509b83a0ab5f4
https://doi.org/10.1016/j.jaad.2020.09.025

DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal

Autor: Emmanuel Mignot, Alexandre Gramfort, Pierrick J. Arnal, Valentin Thorey, Stanislas Chambon

Publikováno v: Journal of Neuroscience Methods
Journal of Neuroscience Methods, 2019, 321, pp.64-78. ⟨10.1016/j.jneumeth.2019.03.017⟩
Journal of Neuroscience Methods, Elsevier, 2019, 321, pp.64-78. ⟨10.1016/j.jneumeth.2019.03.017⟩

Background Electroencephalography (EEG) monitors brain activity during sleep and is used to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so-called sleep stages, which are assigned by experts to every 30s window

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d65132519ce1e1d95fd36fac70bcf03
https://pubmed.ncbi.nlm.nih.gov/30946878

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

Autor: Gilles Wainrib, Pierrick J. Arnal, Mathieu Galtier, Alexandre Gramfort, Stanislas Chambon

Publikováno v: IEEE Transactions on Neural Systems and Rehabilitation Engineering
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Institute of Electrical and Electronics Engineers, 2018, 26 (4), pp.17683810. 〈https://ieeexplore.ieee.org/document/8307462/〉. 〈10.1109/TNSRE.2018.2813138〉
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018, 26 (4), pp.17683810. ⟨10.1109/TNSRE.2018.2813138⟩
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Institute of Electrical and Electronics Engineers, 2018, 26 (4), pp.17683810. ⟨10.1109/TNSRE.2018.2813138⟩

International audience; Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of signal a sleep stage, based on the visual in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6200721508d9448c03fb5d80432f0704
https://hal.archives-ouvertes.fr/hal-01810436/file/1707.03321.pdf