Comprehensive Summary
Epilepsy is a field where there is uncertainty in diagnostics. Due to this, diagnoses of epilepsy can vary, which affects the reproducibility of the diagnosis. The review examines electronic records with electroencephalography (EEG), magnetic resonance imaging (MRI), and history-taking. Artificial intelligence can determine the efficiency of task automation and improvements in diagnostic accuracy. Although this model uses artificial intelligence, its biases are also discussed. The results state that artificial intelligence should support clinical judgment and not replace a physician's diagnosis or treatment protocol. Improvements in diagnosis strategies can help to make diagnosis for patients with epilepsy more effective and be applied to different applications.
Outcomes and Implications
This is important for the medical community because epilepsy has a lot of variation in diagnoses. An artificial intelligence model can support a physician's judgment and confirm if the patient has epilepsy. This is valuable to the medical community as artificial intelligence can efficiently improve upon medical diagnosis and treatment protocols.