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Hugo Fitipaldi is a postdoctoral fellow at the Department of Clinical Sciences at Lund University. He received his BSc in Physiotherapy from Universidade Federal de Pernambuco in 2013, followed by an MPH from Lund University in 2018. In 2023, he completed his PhD in Genetic Epidemiology at the Lund University Diabetes Centre, where he focused on the application of data mining and artificial intelligence to derive public health evidence from large health datasets.

As a postdoctoral fellow, Hugo applies data mining and AI-based frameworks to structured and unstructured health datasets, with a focus on epidemiology, public health, and systems medicine. His work is part of the EU-funded projects BEAt-DKD and PRIME-CKD, where he uses AI to identify and validate prognostic and predictive biomarkers for rapid aggressive disease progression in diabetic kidney disease (DKD) and identify potential targets for new drugs.

Hugo's research interests lie in the integration of "big data" from various sources (OMICS, registers, surveys, etc.) to derive meaningful information that can potentially help future decision-making for healthcare. 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

UKÄ subject classification

  • Medical and Health Sciences

Free keywords

  • Machine Learning
  • Artificial intelligence
  • Deep learning
  • Epidemiology
  • LUDC


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Collaborations and top research areas from the last five years

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