https://www.scipedia.com/public/Perez-Agudelo_et_al_2022a Wed, 01 Jun 2022 13:03:26 +0200 https://www.scipedia.com/public/Perez-Agudelo_et_al_2022a Artificial intelligence is a broad branch of computer science that enables the creation of analysis pathways that mimic human intelligence; it is a set of adaptive tools that can be used to predict outcomes from biological and clinical data. Artificial intelligence models have the potential to improve the efficiency of healthcare by integrating information including adverse drug events. Objective. To apply artificial intelligence techniques to adverse event and medication use information reported for the Colombian population. Methodology. Non-interventional research, with an analytical and retrospective component. The methods included data science mediated by artificial intelligence techniques. Study population: patients with national adverse event reporting between 2017 and 2019 available in the Colombia open data platform. Results. Female sex had a representation of 59.65% of the adverse events reported. The largest number of patients presented an outcome or exit type "recovered resolved" in 40.4%. The most common route of administration was the oral route (27.85%). The artificial intelligence algorithm allowed predictions close to 90% regarding recovery from an adverse reaction. Conclusion. The inclusion of artificial intelligence for the analysis of the variables: gender, adverse reaction recovery, route of administration, mechanism of the reaction, types of ADR and age of onset, allows the creation of a predictive tool that anticipates the presentation of possible outcomes related to the prescription of a drug.

]]> Juan Manuel Pérez-Agudelo https://www.scipedia.com/public/Zuluaga_et_al_2020a Sun, 12 Apr 2020 16:18:29 +0200 https://www.scipedia.com/public/Zuluaga_et_al_2020a Pharmacology is taught in medical schools in the years of basic science and in the transition to the clinical field, this science is in charge of studying the interactions between drugs and living matter; at the time of medical practice it teaches how a chemical substance (active principle) has benefits and helps to improve certain pathologies, as well as which substances should not be used. The teaching of this subject is a process of great importance in the introduction of students to clinical practice and their subsequent professional development. Although the importance of this subject in the medical field is taken into account, the learning gaps and the lack of theoretical-practical correlation on the part of students become evident, since when it comes to focusing knowledge on problem solving, very few students have an adequate picture of what is the most appropriate management in a specific scenario. It has been observed for several years that the educational process of pharmacology and therapeutics is not enough, and this is evidenced by the fact that the conceptual gaps of medical students and medical graduates are found. This global review of the education-learning process focuses on the most used pedagogical elements and which are most appropriate to impact on learning, solid understanding and depth of both pharmacological terminology and concepts and their applicability to achieve academic and professional competence.