M
Manoel Horta Ribeiro
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 46
Citations - 1531
Manoel Horta Ribeiro is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Population & Pandemic. The author has an hindex of 11, co-authored 46 publications receiving 683 citations. Previous affiliations of Manoel Horta Ribeiro include Universidade Federal de Minas Gerais.
Papers
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Journal ArticleDOI
Automatic diagnosis of the 12-lead ECG using a deep neural network
Antônio H. Ribeiro,Antônio H. Ribeiro,Manoel Horta Ribeiro,Gabriela M. M. Paixão,Derick M. Oliveira,Paulo R. Gomes,Jéssica A. Canazart,Milton P. S. Ferreira,Carl R. Andersson,Peter W. Macfarlane,Wagner Meira,Thomas B. Schön,Antonio Luiz Pinho Ribeiro +12 more
TL;DR: Results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice.
Journal ArticleDOI
Automatic diagnosis of the 12-lead ECG using a deep neural network
Antônio H. Ribeiro,Antônio H. Ribeiro,Manoel Horta Ribeiro,Gabriela M. M. Paixão,Derick M. Oliveira,Paulo R. Gomes,Jéssica A. Canazart,Milton P. S. Ferreira,Carl R. Andersson,Peter W. Macfarlane,Wagner Meira,Thomas B. Schön,Antonio Luiz Pinho Ribeiro +12 more
TL;DR: In this paper, a deep neural network (DNN) was used to detect 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%.
Proceedings ArticleDOI
Auditing radicalization pathways on YouTube
TL;DR: In this article, the authors conduct a large-scale audit of user radicalization on YouTube, and analyze 330,925 videos posted on 349 channels, which they broadly classified into four types: Media, Alt-lite, the Intellectual Dark Web (I.D.W.), and the Alt-right.
Proceedings Article
Characterizing and Detecting Hateful Users on Twitter.
TL;DR: This work develops and employs a robust methodology to collect and annotate hateful users which does not depend directly on lexicon and where the users are annotated given their entire profile, and forms the hate speech detection problem as a task of semi-supervised learning over a graph, exploiting the network of connections on Twitter.
Posted Content
Auditing Radicalization Pathways on YouTube
TL;DR: A large-scale audit of user radicalization on YouTube shows that the three channel types indeed increasingly share the same user base; that users consistently migrate from milder to more extreme content; and that a large percentage of users who consume Alt-right content now consumed Alt-lite and I.D.W. content in the past.