TBM-App: a clinical decision support system for tuberculous meningitis
| Autor: | Lucas Santos de Oliveira, Luiz Ricardo Albano dos Santos, Filipe Andrade Bernardi, Antonio R-Netto, Matheus Angerami Marçal, Lívia Maria Pala Anselmo, Carla Cristina Buri da Silva, Rui Rijo, Domingos Alves, Nathalia Yukie Crepaldi, Gabriela Cristina Silva Prado, Valdes Roberto Bollela, Fernanda S Merli |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
Tuberculosis Computer science 020206 networking & telecommunications Context (language use) 02 engineering and technology Disease medicine.disease Clinical decision support system Tuberculous meningitis Clinical Practice Acquired immunodeficiency syndrome (AIDS) 0202 electrical engineering electronic engineering information engineering medicine General Earth and Planetary Sciences 020201 artificial intelligence & image processing Intensive care medicine General Environmental Science |
| Zdroj: | Procedia Computer Science. 164:565-572 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2019.12.221 |
| Popis: | Tuberculosis (TB) was responsible for approximately 1.6 million deaths in 2017 and it is the deadliest among the infectious diseases, killing more than Acquired Immunodeficiency Syndrome (AIDS) related diseases. One of the most lethal forms of this disease is the central nervous system TB. The clinical and microbiological diagnosis of tuberculous meningitis (TBM) is still a challenge and to standardize the diagnosis and offer more reliable information to the decision-making process in the clinical practice, predictive scores were created and adapted for the Brazilian context. The score implementation will require staff training but has the potential to reduce time to the TBM diagnosis and therefore start correct treatment early. Although, there is a need to increase the access to the score and to facilitate its use among physicians to save time and resources. This study shows the design and development of a multiplatform mobile application to calculate the predictive score for tuberculous meningitis, in order to support clinical decisions. The preliminary results have shown an effective and versatile App, available to a variety of devices and which can still be available in places with limited or no internet access. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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