Diploma in Artificial Intelligence for Health Informatics

To train specialists in the theoretical and practical aspects of data analysis and data science, capable of collecting, cleaning, analyzing and distilling the information contained in the databases of health institutions.
$ 40,000 MXN
/ 196 hours

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The distilled information will be used to generate and share knowledge in an effective way to test hypotheses proposed by health specialists and support decision makers in the design of strategies and public policies to improve health care. The program emphasizes the formation and integration of multidisciplinary work teams formed by data engineers, data analysts and data scientists, specialists in data intelligence for health and experts in health sciences to develop projects aimed at solving priority health problems of the Mexican population. The Diploma will last four trimesters, and will be taught annually starting in August 2023.

. Profile of applicants to the diploma course
The diploma is aimed at members of the Mexican health system in charge of the management, use and distillation of information and knowledge of health databases from different sources and modalities, such as electronic medical records, results of diagnostic tests and medical examinations.

. Syllabus
The curriculum includes fundamental concepts for healthcare data science and analytics, as well as methodologies for machine learning, deep learning and other artificial intelligence techniques.

First quarter (48 h)
Overview of Artificial Intelligence for Health Informatics (4 h)

1. Machine learning and artificial intelligence applications
Introduction to Programming: Basic Concepts of R (32 h)
Fundamentals of Probability and Statistics for Health Informatics (16 h)

Second trimester (48 h)
Applied Medical Statistics (32)
Narrative for Data Science (16)

Article Analysis Workshop.

Third quarter (48 h)
Machine Learning for Health Informatics (48 h)

Introduction to Deep Learning.
Fourth quarter (48 h)
Artificial Intelligence for Health Informatics.

The curriculum will be taught by researchers attached to the Computational Science and Engineering Group and the Molecular Biology Division of IPICYT, as well as other national and international institutions that are part of the Multidisciplinary Alliance of Health Specialists of the Mobile Health Center of IPICYT (https://mhc.ipicyt.edu.mx/mobilehealthcenter/).



Rubén López-Revilla. He is a professor of the Molecular Biology Division (DBM) of IPICYT, a medical doctor from the Universidad Autónoma de San Luis Potosí, and has a PhD in Genetics from the Centro de Investigación y de Estudios Avanzados. He is a member of the National System of Researchers Level 2. He founded the DBM-IPICYT. His research interests are the diagnosis and molecular epidemiology of infectious diseases and cancer and the monitoring of indoor air quality to prevent COVID-19 and other airborne diseases. In collaboration with Salvador Ruiz Correa he initiated the Mobile Health Center, a multidisciplinary action-research group that addresses priority public health problems with informatics tools and mobile applications.



Ana Paulina Ponce Tadeo. She holds a B.Sc. in Physics and a M.Sc. in Science from the Universidad Autónoma de San Luis Potosí, PhD in Nanosciences and Materials from IPICYT. Her line of research focuses on the structural properties of small magnetic aggregates of the 3d and 4d series using first principles calculations and graph theory. In addition, he has been a senior lecturer for 6 years at the Polytechnic University of San Luis Potosi where he teaches Mathematics. He is currently a postdoctoral fellow in the Advanced Materials Division and is a member of the Computational Science and Engineering Group of IPICYT.


Cesare Moises Ovando Vazquez. D. in Science with a major in Physics from Cinvestav Zacatenco. He is a member of the National System of Researchers Level II. His research is in Bioinformatics and Artificial Intelligence (AI) applied to the study of cross-kingdom RNAs and metabolic syndrome (MetS). He currently directs the Bioinformatics and AI laboratory (AI-BioLab) CNS-IPICYT.
Salvador Ruiz Correa. CNS Researcher. B.S. and M.S. in Mechanical and Electrical Engineering from the Universidad Nacional Autónoma de México and Ph.D. in Electrical Engineering from the University of Washington in Seattle. He is a member of the National System of Researchers Level I since 2008. His research interests focus on mobile computing applications, artificial intelligence and statistics applied to social impact projects in Mexico. He directs the Youth Innovation Laboratory (You-i Lab) at IPICYT.


Daniel Ignacio Salgado Blanco. D. in Materials Science and Engineering from the National Autonomous University of Mexico (UNAM). He is currently working as a CONACYT professor attached to the CNS-IPICYT. His research interests are linked to the study of colloidal systems through molecular simulations, using high performance computing. He is a member of the National System of Researchers Level I.
Mishael Sánchez Pérez. He holds a degree in Computer Engineering and Computer Networks from the Universidad Morelos de Cuernavaca and a PhD in Computer Science from ITESM. His research focuses on massive data analysis using Machine Learning and bioinformatics tools.


Necesidades que resuelve

Las metas principales de los estudiantes participante son tres:
● Adquirir los conocimientos básicos que sustentan la teoría y la práctica de la IA.
● Tener la capacidad de utilizar las herramientas básicas en la IA para la solución de problemas prácticos en el área de la salud que requieren el procesamiento de datos y el destilado de información.
● Tener los conocimientos básicos para acceder a un clúster de supercómputo y usar su infraestructura para la resolución de un problema sencillo, pero fácilmente escalable, donde se aplique el aprendizaje profundo.

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