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Artificial intelligence and machine learning in human diseases

19th national competition for scientific and technical research

Rare diseases

Senior Researcher : Pablo Lapunzina Badía

Research Centre or Institution : INGEMM-Hospital Universitario La Paz-CIBERER. Madrid

Abstract

The objectives of this work are to provide primary information on the signs, symptoms and findings of each of the more than 20,000 human diseases and the adverse effects of more than 12,000 drugs and pharmaceutical compounds for human treatments; to integrate them into a database of free access, to prioritize them by age of appearance (in 7 levels) and by frequency (in 4 levels), in order to: 1) provide the health systems of any part of the world with quality primary information on all diseases human, its signs, symptoms and findings (biochemical, radiological, others) so that they can be used as diagnostic help in any medical act and 2) offer intelligent data systems of big data (through artificial intelligence and machine learning) tools for processing clinical information in a standardized  format that is capable of being recognized by computerized systems and that can be useful in the analysis of high-performance exomic and genomic studies.

The project is divided into 3 well-differentiated methodological phases. The first part consists of the algorithms and search engines aimed at capturing and preparing the information that should be reviewed and curated. The second phase is the incorporation of all the information obtained in a web tool where it can be curated by the experts. The third phase is the design and implementation of a diagnostic aid tool in web format.

 

Scientific Production
 
Magazine Articles 1
Communications at national conferences 1
Communications at international conferences 1

 

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