Artificial neural network: A data mining tool in pharmacovigilance
Introduction: Pharmacovigilance ensures patient safety as well as drug safety. In India, there is still a lot to be done and learned to ensure that the work and activities done in the area of pharmacovigilance are safely implemented. The key issue in India is that adverse drug reaction (ADR) has been underreported. The number of patients who are hospitalized is growing due to adverse drug effects and figuring out the exact cause of ADRs is a problem, if a patient is treated concurrently with several medicines.
Methods: In the analysis, we will analyze the various types of evaluation scale to conduct the ADR evaluation and identify the trigger agents. For situations where various approaches may not be adequate prognostic models, neural networks emerged as advanced data processing devices.
Results: However, it is essentially statistical modeling tools that are used in neural network models, as the term implies.
Conclusions: These models are thus a replacement solution, offering resources that learn by themselves, while not requiring experts or advanced computer programs, to solve problems and discern patterns.
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