Artificial Intelligence approaches to predict COVID-19 infection in Senegal.

The SARS-CoV2 virus, which causes COVID-19 (coronavirus disease) has become a pandemic and has expanded all over the world. Because of increasing number of cases day by day, it takes time to interpret the data thus the limitations in terms of both treatment and findings are emerged. Due to such limitations, the need for clinical decisions making system with predictive algorithms has arisen.

Iconic Visualization of Sickle Cell Patients Current and Past Health Status.

Rapid access to patient overall health status is essential for a physician during a medical consultation. The use of a HIS for the management of neonatal screening and follow-up of sickle cell disease patients at CERPAD in the Saint-Louis region of Senegal leads the patient electronic records growing in volume and complexity. To facilitate access to relevant information and shortens the time required to analyze and understand these clinical data, an original solution is to set up a data visualization system.

SIMENS-LIS4SC, a Laboratory Information System for Biological Tests of Sickle Cell Screening and Healthcare.

Neonatal screening and ongoing follow-up of children with sickle cell disease are essential to reduce the mortality caused by this disease. To ensure care continuity, it is essential to include in the patient's record the history and details of biological tests. Thus, it is necessary to provide a Laboratory Information System for electronic management of biological test prescription and results, and the laboratory system must integrate well with Health Information Systems.

Model-Driven Architecture Based Software Development for Epidemiological Surveillance Systems.

Epidemiological surveillance systems enable collection, analysis and dissemination of information on the monitored disease to different stakeholders. It may be done manually or using a software. Given the poor performances of manual systems, the software approach is generally adopted.

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improvement of the surveillance system for these diseases. Biomedical ontologies are a growing field that can improve health information systems. Indeed biomedical ontologies allow semantic support, data integration, automated reasoning.

Towards an Information System for Sickle Cell Neonatal Screening in Senegal.

Sickle cell disease is a major public health problem in Senegal. It is an inherited disease that affects about 300,000 births worldwide each year. There are 70 million people affected worldwide, 80% of whom live in sub-Saharan Africa.

Communicable and non-communicable disease risks at the Grand Magal of Touba: The largest mass gathering in Senegal.

Background: An estimated 4-5 million individuals gather each year in the holy city of Touba, Senegal during the Grand Magal religious pilgrimage. Pilgrims come from across Senegal and the surrounding countries, as well as from countries outside Africa. It is the largest mass gathering (MG) of the Mouride community and the largest Muslim religious MG in West Africa.

A National Medical Information System for Senegal: Architecture and Services.

In Senegal, great amounts of data are daily generated by medical activities such as consultation, hospitalization, blood test, x-ray, birth, death, etc. These data are still recorded in register, printed images, audios and movies which are manually processed. However, some medical organizations have their own software for non-standardized patient record management, appointment, wages, etc.

Design of schistosomiasis ontology (IDOSCHISTO) extending the infectious disease ontology.

Epidemiological monitoring of the schistosomiasis' spreading brings together many practitioners working at different levels of granularity (biology, host individual, host population), who have different perspectives (biology, clinic and epidemiology) on the same phenomenon. Biological perspective deals with pathogens (e.g.