SSEM (Syndemic and Syndemogenesis Elements Modeler) is a C++, Python and CUDA (Compute Unified Device Architecture) program that is used to do syndemic and syndemogenesis network and statistical analysis in medicine. SSEM was developed as a collaboration between the Universidad Nacional Autónoma de México, he Latin American Study Group of Rheumatic Diseases in Indigenous Peoples (GLADERPO) and the Colegio Mexicano de Reumatología A.C


The basics of data, big data, and machine learning in clinical practice
Clinical Rheumatology
2020 | journal-article
DOI: 10.1007/s10067-020-05196-z

Syndemic and syndemogenesis of low back pain in Latin-American population: a network and cluster analysis
Clinical Rheumatology
2020 | journal-article
DOI: 110.1007/S10067-020-05047-X

Epidemiology and socioeconomic impact of the rheumatic diseases on indigenous people: An invisible syndemic public health problem
Annals of the Rheumatic Diseases
2018 | journal-article
DOI: 10.1136/annrheumdis-2018-213625

SSEM components

Descriptors calculated by SSEM

Multi level correlations
Quantification values of models
Network relation between subjects
Network relations between variables
Traditional statistical values
Categorical representation of the data


Participating researchers

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