Data Management in Biomedicine

  • LECTURER: Víctor Maojo


Applications of Artificial Intelligence in medicine began at the beginning of the 1970s, centered at its inception on knowledge-based systems. Two decades later, various limitations of this approach caused the area to partially shift focus towards data-centered applications. The different -omics projects that appeared after the Human Genome Project and the increasingly available electronic health records, clinical trials data as well as a huge number of data resources available over the Web led to directions such as Big Data-related research, among others. In this seminar we will see this evolution, main different approaches, methods and techniques for data management in biomedicine, and its advantages and limitations.


  1. Knowledge and data-centered artificial intelligence in biomedicine
  2. Special characteristics of data management in biomedicine
  3. Study designs
  4. Data collection and mining in biomedicine: approaches and techniques
  5. Quality of datasets and results
  6. Limitations of data management in biomedicine
  7. Grand challenges in the area

Assessment Method

Attendance and assignment

Lective hours



  • 03 March, 15:00-18:00

Lecture Theatre

  • A-6305

Tuition Language