Why M.A.T.H Consortium?

Although possible, applying Data Science in Health research presents a very hard challenge to be done alone. Collaboration brings together a sum of capabilities that no one in the group has by itself. This sensibly improves quality and impact of solutions produced.

As with most discoveries, the group almost created itself by chance, when the founders met and start to share similar interests for Data Science applied to health. From similar interests the Consortium evolve to a global initiative with partners distributed in different parts of the globe.

A major challenge in healthcare is its interdisciplinary nature. Our members have complementary training in different areas of knowledge as: Epidemiology, Statistics, Psychology, Business Administration, Geography, and Computer Science. All areas of expertise are applied to the context of health.

Capabilities

M.A.T.H. incorporates a hard to find complementary set of skills to face the information age ever-increasing volume of data.

Healthcare Data Analytics

Healthcare Data Analytics is the discipline dedicated to integrate knowledge from Statistics, Computer Science and Health Sciences to create insights from data.

GIS

Geographic Information Systems are powerful tools capable to explain why health phenomenons occur in specific locations.

Mobile Health (mHealth)

mHealth refers to the provision of health services remotely, built on technologies such as the mobile internet, smart wearable devices, electronic medical records, telehealth, cloud computing and smartphones.

Healthcare Performance Assessment

Healthcare quality monitoring is essential to promote a debate about potential improvements related to care offer process.

Measurement and Modeling

Our goal is also to increment the measurement process by advocating for the use of technology in mobile technology for subjective evaluation, computerized adaptive testings, dynamic testings and stealth assessments.

Text Mining

The ability to extract good quality information from text in a reproducible format is essential for the application of analytics for health.

Research structure


Healthcare data warehouse

We have data from several primary and secondary sources related to health services in Brazil. Our databases cover topics as: health care structure, work process, users satisfaction, population based studies, epidemiological surveillance, procedures performed and much more. The datasets range from primary care to high complexity attention covering public and private organizations.

High capacity processing servers

Working with Big Data and Artificial Intelligence demands high computational power. We have dedicated servers capable of handling large datasets, as well as capability to support the training, prediction and visualization solutions based on artificial intelligence.

Value creation and problem solving orientation

Our team of experts could provide methodological support to approach academic knowledge to solve real world problems. Our members had more than ten years of experience in consulting and research projects dedicated to provide solutions to real world problems.

Team

THIAGO ROCHA

THIAGO ROCHA

PhD

Applied researcher with experience in machine learning, mHealth, healthcare monitoring, business administration, data visualization, and health geographics.

DANTE ALMEIDA

DANTE ALMEIDA

BSc

Generalist full stack software developer with quantitative research and survey theory specializations. Experienced in big data processing, geoprocessing and data analysis.

JOÃO VISSOCI

JOÃO VISSOCI

PhD

Main interests lies in research methods and processes with emphasis on mixed-methods studies for global health, health analytics, Big Data, machine learning, Geospatial artificial intelligence, and applied data science.

REJANE QUEIROZ

REJANE QUEIROZ

PhD

Has experience in the area of Public Health, with emphasis on Dentistry in Public Health, Family Health, Epidemiology, Surveillance and Oral Cancer.

Núbia Rocha

Núbia Rocha

PhD

Applied researcher with experience in data vizualization, geoprocesing, healthcare monitoring and assessment, performance assessment, and business administration.

Catherine Staton

Catherine Staton

MD, MsGH

Catherine's research is focused on the trauma and injury care as well as health disparities amount injury patients.

Erika Thomaz

Erika Thomaz

PhD

Interest in Epidemiology and Statistical Methods Applied to Public Health Research, geoprocessing, forecasting and multilevel modeling.

Luciano Andrade

Luciano Andrade

PhD

Research focus on geoprocessing technologies, mobile devices, access barriers and health infrastructure of emergency and urgency services.

Partners