World's Best Scientists 2026 revealed!

Overview

Adriano Veloso is affiliated with the Universidade Federal de Minas Gerais in Brazil. Their research work primarily spans the fields of Medicine and Computer Science, with a notable focus on Artificial Intelligence, Molecular Biology, Infectious Diseases, Radiology, Nuclear Medicine and Imaging, and Surgery.

The scientist's research interests are reflected in their frequent publication topics, which include COVID-19 diagnosis using AI, Machine Learning in Healthcare, Biomedical Text Mining and Ontologies, Hip disorders and treatments, Explainable Artificial Intelligence (XAI), COVID-19 Clinical Research Studies, and Alzheimer's disease research and treatments.

Adriano Veloso has collaborated extensively with several researchers. Frequent coauthors include Daniella Castro Araújo, Karina Braga Gomes, Nívio Ziviani, Gianlucca Zuin, and Daniel Ciampi de Andrade.

The venues where they have frequently published consist of:

  • arXiv (Cornell University)
  • 2022 International Joint Conference on Neural Networks (IJCNN)
  • Ultrasound in Obstetrics and Gynecology
  • SSRN Electronic Journal
  • Artificial Intelligence in Medicine

Recent papers authored or coauthored by Adriano Veloso include:

  • "Understanding machine learning software defect predictions" (2020), Automated Software Engineering
  • "Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models" (2021), Journal of Endocrinological Investigation
  • "Finding reduced Raman spectroscopy fingerprint of skin samples for melanoma diagnosis through machine learning" (2021), Artificial Intelligence in Medicine
  • "Prediction of SARS-CoV-2-positivity from million-scale complete blood counts using machine learning" (2022), Communications Medicine
  • "A Novel Panel of Plasma Proteins Predicts Progression in Prodromal Alzheimer's Disease" (2022), Journal of Alzheimer s Disease

Best Publications

  • Supervised Learning for Fake News Detection

    Julio C. S. Reis;Andre Correia;Fabricio Murai;Adriano Veloso

  • Dengue surveillance based on a computational model of spatio-temporal locality of Twitter

    Janaína Gomide;Adriano Veloso;Wagner Meira;Virgílio Almeida

  • Lazy Associative Classification

    Adriano Veloso;Wagner;Mohammed Zaki

  • From bias to opinion: a transfer-learning approach to real-time sentiment analysis

    Pedro Henrique Calais Guerra;Adriano Veloso;Wagner Meira;Virgílio Almeida

  • Reverse Engineering Socialbot Infiltration Strategies in Twitter

    Carlos Freitas;Fabricio Benevenuto;Saptarshi Ghosh;Adriano Veloso

  • Multiobjective Pareto-Efficient Approaches for Recommender Systems

    Marco Tulio Ribeiro;Nivio Ziviani;Edleno Silva De Moura;Itamar Hata

  • Pareto-efficient hybridization for multi-objective recommender systems

    Marco Tulio Ribeiro;Anisio Lacerda;Adriano Veloso;Nivio Ziviani

  • Effective self-training author name disambiguation in scholarly digital libraries

    Anderson A. Ferreira;Adriano Veloso;Marcos André Gonçalves;Alberto H.F. Laender

  • Mining Frequent Itemsets in Evolving Databases.

    Adriano Veloso;Wagner Meira;Márcio de Carvalho;Bruno Pôssas

  • Multi-label Lazy Associative Classification

    Adriano Veloso;Wagner Meira;Marcos Gonçalves;Mohammed Zaki

  • Learning to rank at query-time using association rules

    Adriano A. Veloso;Humberto M. Almeida;Marcos A. Gonçalves;Wagner Meira

  • Understanding machine learning software defect predictions

    Geanderson Esteves;Eduardo Figueiredo;Adriano Veloso;Markos Viggiato

  • Explainable Machine Learning for Fake News Detection

    Julio C. S. Reis;André Correia;Fabrício Murai;Adriano Veloso

  • Learning to rank for content-based image retrieval

    Fabio F. Faria;Adriano Veloso;Humberto M. Almeida;Eduardo Valle

  • Parallel and distributed methods for incremental frequent itemset mining

    M.E. Otey;S. Parthasarathy;Chao Wang;A. Veloso

  • Effective sentiment stream analysis with self-augmenting training and demand-driven projection

    Ismael Santana Silva;Janaína Gomide;Adriano Veloso;Wagner Meira

  • Cost-effective on-demand associative author name disambiguation

    Adriano Veloso;Anderson A. Ferreira;Marcos André Gonçalves;Alberto H. F. Laender

  • Demand-driven tag recommendation

    Guilherme Vale Menezes;Jussara M. Almeida;Fabiano Belém;Marcos André Gonçalves

  • Mining frequent itemsets in distributed and dynamic databases

    M.E. Otey;C. Wang;S. Parthasarathy;A. Veloso

  • Automated Essay Scoring in the Presence of Biased Ratings

    Evelin Amorim;Marcia Cançado;Adriano Veloso

Frequent Co-Authors

Wagner Meira
Wagner Meira Universidade Federal de Minas Gerais
Nivio Ziviani
Nivio Ziviani Universidade Federal de Minas Gerais
Marcos André Gonçalves
Marcos André Gonçalves Universidade Federal de Minas Gerais
Srinivasan Parthasarathy
Srinivasan Parthasarathy The Ohio State University
Mohammed J. Zaki
Mohammed J. Zaki Rensselaer Polytechnic Institute
Alberto H. F. Laender
Alberto H. F. Laender Universidade Federal de Minas Gerais
Fabrício Benevenuto
Fabrício Benevenuto Universidade Federal de Minas Gerais
Virgilio Almeida
Virgilio Almeida Universidade Federal de Minas Gerais
Jussara M. Almeida
Jussara M. Almeida Universidade Federal de Minas Gerais
Edleno Silva de Moura
Edleno Silva de Moura Federal University of Amazonas

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