Development, assessment and educational impact of a blended e-learning training program on pharmacovigilance implemented in four African countries.

Introduction: Efforts to improve medication access in low-and middle-income countries, particularly in Sub-Saharan Africa, have made progress, especially in the fight against infectious diseases such as tuberculosis. However, challenges exist in establishing effective pharmacovigilance systems. The PhArmacoVIgilance Africa (PAVIA) project was committed to enhancing pharmacovigilance in Tanzania, Eswatini, Nigeria, and Ethiopia, with an emphasis on anti-tuberculosis drugs, utilizing various methods, including training.

Mining approximate temporal functional dependencies with pure temporal grouping in clinical databases.

Functional dependencies (FDs) typically represent associations over facts stored by a database, such as "patients with the same symptom get the same therapy." In more recent years, some extensions have been introduced to represent both temporal constraints (temporal functional dependencies - TFDs), as "for any given month, patients with the same symptom must have the same therapy, but their therapy may change from one month to the next one," and approximate properties (approximate functional dependencies - AFDs), as "patients with the same symptomgenerallyhave the same therapy." An AFD holds most of the facts stored by the database, enabling some data to deviate from the defined property: the percentage of data which violate the given property is user-defined.