Dr. Rafael Martínez Tomás. Universidad Nacional de Educación a Distancia (UNED) (Spain)

Dr. Mariano Rincón Zamorano. Universidad Nacional de Educaciónm a Distancia (UNED) (Spain)


In the last decades there has been an overwhelming growth of both the amount of sensorized and stored data and the processing machines’ capacity. Automatic data analysis must play a very important role because it is the only way to deal with the growing complexity. Medicine has not been alien to this movement and there is an intense work in the automatic analysis of recorded data of different nature and formats (clinical histories, epidemiological and socio-demographic data, diagnostic tests, medical images, genetic markers, etc.).

There is no doubt that the field of health sciences is a field of high social interest and, at the same time, a very eclectic mix with great possibilities for experimental research at the frontier of knowledge. It is a good scenario for testing advanced reasoning and learning techniques able to combine and integrate information from different sources, from text in natural language to specific encodings and ontological models. The aim of this session is to provide a forum to discuss about progress on the field of artificial intelligence applied to the health sciences (mental, social and physical health).

Specific topics for this special session include, but are not limited to:

  • computational intelligence in medicine
  • machine learning methods in medicine (supervised, semisupervised or unsupervised, meta-learning, reinforcement, deep learning, transfer learning, fuzzy learning)
  • automated reasoning and meta-reasoning
  • temporal reasoning and learning
  • relational data analysis
  • bayesian methods for reasoning and machine learning
  • fusion and exploitation of heterogeneous data sources
  • planning and decison making in medicine
  • test mining
  • medical knowledge engineering
  • intelligent modeling and management of healthcare pathways and clinical guidelines