The seedbed of artificial intelligence in health seeks to generate spaces for discussion, where from the problems that can be found in the areas of medicine and health sciences, and possible solutions from the engineering area can be merged to find viable solutions. At the same time, through the seedbed seeks to inform students and professionals in the area of artificial intelligence that is increasingly used in different fields, being considered transversal for many sciences.

Research Lines:

Mainly, but not limited to:

• Analysis of physiological phenomena through the use of biosignal processing.
• Motion analysis from pose models.
• Bioinformatics and Artificial Intelligence (in conjunction with SyNERGIA).
• Health Data Science.
• Diagnostic Support Systems.
• Machine and Deep Learning.
• Natural Language Processing.

Objectives:

1. To encourage the study of existing techniques in artificial intelligence with the purpose of applying them in the solution of problems in the field of health.
2. Establish solutions in the area of medicine and health sciences through different paradigms of artificial intelligence.
3. To generate new alternatives for the creation of artificial intelligence models based on bio-inspired systems.
4. To establish spaces for meeting different disciplines for joint interdisciplinary work in solution to health problems.

The seedbed of artificial intelligence in health seeks to generate spaces for discussion, where from the problems that can be found in the areas of medicine and health sciences, and possible solutions from the engineering area can be merged to find viable solutions. At the same time, through the seedbed seeks to inform students and professionals in the area of artificial intelligence that is increasingly used in different fields, being considered transversal for many sciences.

Research Lines:

Mainly, but not limited to:

• Analysis of physiological phenomena through the use of biosignal processing.
• Motion analysis from pose models.
• Bioinformatics and Artificial Intelligence (in conjunction with SyNERGIA).
• Health Data Science.
• Diagnostic Support Systems.
• Machine and Deep Learning.
• Natural Language Processing.

Objectives:

1. To encourage the study of existing techniques in artificial intelligence with the purpose of applying them in the solution of problems in the field of health.
2. Establish solutions in the area of medicine and health sciences through different paradigms of artificial intelligence.
3. To generate new alternatives for the creation of artificial intelligence models based on bio-inspired systems.
4. To establish spaces for meeting different disciplines for joint interdisciplinary work in solution to health problems.