Mr Marcos del Pozo Banos

Senior Research Analyst
Medicine
Telephone: (01792) 604094
Email: JavaScript is required to view this email address.

My main areas of interest are mental health informatics and artificial intelligence.

Areas of Expertise

  • Artificial Intelligence
  • Health Informatics
  • Mental Health

Publications

  1. DelPozo-Banos, M., Travieso, C., Alonso, J., John, A., del Pozo Banos, M. Evidence of a Task-Independent Neural Signature in the Spectral Shape of the Electroencephalogram International Journal of Neural Systems 28 01 1750035
  2. Del Pozo-Banos, M., Alonso, J., Ticay-Rivas, J., Travieso, C., del Pozo Banos, M. Electroencephalogram subject identification: A review Expert Systems with Applications 41 15 6537 6554
  3. Travieso, C., Ticay-Rivas, J., Briceño, J., del Pozo-Baños, M., Alonso, J., del Pozo Banos, M. Hand shape identification on multirange images Information Sciences 275 45 56
  4. del Pozo-Baños, M., Ticay-Rivas, J., Alonso, J., Travieso, C., del Pozo Banos, M. Features extraction techniques for pollen grain classification Neurocomputing 150 377 391
  5. Travieso, C., Pozo-Baños, M., Alonso, J., del Pozo Banos, M. Fused intra-bimodal face verification approach based on Scale-Invariant Feature Transform and a vocabulary tree Pattern Recognition Letters 36 254 260

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Teaching

  • PMIM102 Scientific Computing and Health Care

    The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate. This is a core / compulsory module and worth 20 Masters level credits. Module leader is Dan Thayer

  • PMIM402 Machine Learning in Healthcare

    Data scientists working in healthcare are called to deal with problems involving classification and pattern recognition. The objective of this module is to provide the essential theory and practical aspects of widely used machine learning software. This is a core/compulsory module of 20 credits. Module leaders are Arron Lacey and Shangming Zhou