Biostatistics & Intelligent Data Analysis

This team has a strong record on both biostatistics and machine learning. The first goal of this group is thus to improve this record and strengthen research in these areas. The second goal of the group is therefore to look beyond traditional biostatistics into modern methods of statistical learning and intelligent data analysis, without losing the necessary formality (e.g. log-linear analysis of big data, Bayesian networks for clinical research and decision support, or information-based data analysis).

Not only current graduation programmes are not prepared for this new setting but, in the health-care domain, specific features of health‑related data are not straightforward, making health data curation a research topic on its own. The holistic nature of this topic makes it a major overseeing research area of the group. The third major goal of the group is thus to assess the need and build an advanced training programme on health data analysis and curation.

Integrated Members

 Armando Teixeira-Pinto    Coralia    Cristina Santos    Cristina Santos    Pedro Rodrigues
Andreia
Teixeira
  Corália
Vicente
  Cristina
Costa-Santos
  Maria Luísa
Castro Guedes
  Pedro Pereira
Rodrigues [PI]

Other PhD Members

  • Armando Rogério Martins Teixeira Pinto
  • Carlos Saez Silvestre
  • João Manuel Portela Gama
  • Myra Spiliopoulou
  • Peter Lucas
  • Teresa Sarmento Henriques
  • Zoran Bosnic

Other researchers

  • Cláudia Camila Rodrigues Pereira Dias
  • Cristiano Inácio Lemes
  • Daniela Filipa Ferreira dos Santos
  • Luís Manuel Ferreira Pinto
  • Mariana Fernandes Lobo
  • Marisa Isabel Garcia Rodrigues
  • Orquídea Maria da Silva Ribeiro
  • Rosa Celeste dos Santos Oliveira
  • Rui António da Cruz Vasconcellos Guimarães
  • Sílvia Inês Castro Moreira
  • Sofia Ribeirinho Soares Ferreira Leite

 

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