Etiology
The etiology is somewhat complicated, as epilepsy entails complex features and is, in certain instances, multifactorial due to genetic predispositions, environmental influences, and risk behavior. There are genes more prone to mutation, and genetic influence is significant in its causation (Bamikole et al., 2019). Other causes may be broadly classified into environmental such as head injuries, brain infections, prenatal injuries, or developmental anomalies that may lead to epilepsy. Substance abuse, sleep deprivation, and stress, among many others, would also exacerbate the condition. These models were conceived so that AI could predict the likelihood of risks like epilepsy in a person using machine learning algorithms. They identify patterns in large sets of genetic data to know the relationship between genetic profiles and environmental exposures. This likely helps in better rates for predicting risk levels; hence, it is much easier for appropriate interventions to be timely, giving rise to personalized care interventions targeting specific patients’ risk profiles. This diverse data set can be used to train AI-based models, for example, genomic information plus environmental factors.
Some new opportunities for studying the etiology of epilepsy include using artificial intelligence (AI) to analyze ecological and genetic data (Nair et al., 2019). This would mean that AI-driven approaches would be based on pinning down the critical risk factors and patterns that would allow taking preventive measures meant to mitigate the onset and progression of epilepsy and avail more effective strategies for its treatment. Thus, the paper raised concerns about optimizing outcomes that individuals affected by this disorder might gain.
Demographics
Globally, people from different walks of life are affected by epilepsy, with an estimated 50 million people around the world suffering from the disease (World Health Organization, 2024). The estimated number of persons with active epilepsy in the general population ranges from 4 to 10 per one thousand (World Health Organization, 2024). In developed countries like the USA, the annual incidence of diagnosed epilepsy is approximately 49 per 100,000. However, this figure can be significantly higher, up to 139 cases per one hundred thousand 100,000 people annually in low and middle-income countries (World Health Organization, 2024). Among others, high incident rates in low-income countries can be explained by factors such as local conditions like malaria or neurocysticercosis being endemic there, increased risk for road traffic injuries, birth trauma, and inequalities in medical infrastructure and access to preventive health programs. It should be noted that about eighty percent (80%) of the global epileptic population resides within developing countries (World Health Organization, 2024). These figures highlight how significant socioeconomic differences have a bearing on epilepsy’s prevalence and incidence worldwide.
Affected organ system
Primarily, epilepsy is a disorder of the brain that significantly affects the central nervous system, the major part being the brain, where it disorganizes the regular activity of the neurons, leading to repeated seizures (World Health Organization, 2024). This can vary according to whether the temporal lobe, the frontal lobe, or the hippocampus is involved, thereby causing complex partial seizures with their peculiar manifestations. Long-standing seizures contribute to the development of structural changes within the brain, such as hippocampal sclerosis, which can further impair a person’s memory and cognitive function over time (Novak et al., 2022). Identification of specific brain areas related to epilepsy is essential in the diagnosis, the proper development of a suitable treatment plan, and the management of the condition in such patients to optimize cognitive function and their overall quality of life.
Physiology and symptoms
In epilepsy, abnormal electrical discharges disrupt the brain’s normal physiology, precipitating seizures (World Health Organization, 2024). Symptoms vary based on seizure type and affected brain regions, commonly including loss of consciousness, convulsions, muscle stiffness, and sensory disturbances. Left untreated, epilepsy can lead to cognitive decline, psychiatric comorbidities, and heightened injury risk during seizures. According to Iqbal & Syed (n.d.), individuals with uncontrolled seizures face elevated mortality rates, with sudden unexpected death in epilepsy (SUDEP) posing a significant concern, emphasizing the critical importance of effective seizure management and treatment strategies in epilepsy care.
Diagnosis, treatment, and AI
The available diagnostic approaches towards epilepsy include a thoroughly taken medical history, examination of, and sometimes even tests like EEG and brain imagining (MRI or CT scan) (Anwar et al., 2020). The therapeutic options are anti-epileptic drugs, surgery for intractable ones, and the adjustment of lifestyle. Some side effects of AEDs, however, do include dizziness, fatigue, or impaired cognition, and they do need to be watched out for. AI has revolutionized the diagnosis and planning for the treatment of epilepsy. Machine learning algorithms are applied to analyze several patterns of EEG for detecting and classifying seizures that facilitate early intervention (Nafea & Ismail, 2022). Predictive models have been developed using AI that involve patient-specific data input for an optimized choice and dosage of AEDs, which would, in turn, minimize adverse effects and optimize the treatment outcome.
The multifactorial nature of epilepsy underlines the importance of a comprehensive approach to diagnosis and treatment. Therefore, advances in artificial intelligence may lead to more effective management of epilepsy, maybe even personalizing the treatment strategy so that patient outcomes will improve. Prospective future integration of artificial intelligence technologies in the clinical practice of epileptology directed at the population living with chronic disorder implies developing and supporting personalized therapeutic strategies. Understanding epilepsy’s complexities and embracing AI-driven solutions empowers patients and healthcare professionals. With ongoing research and technological advancements, the future looks promising for those living with epilepsy.
References
Anwar, H., Khan, Q. U., Nadeem, N., Pervaiz, I., Ali, M., & Cheema, F. F. (2020). Epileptic seizures. Discoveries, 8(2).
Bamikole, O. J., Olufeagba, M. D. B., Soge, S. T., Bukoye, N. O., Olajide, T., Ademola, S. A., & Amodu, O. K. (2019). Genetics of epilepsy. J Neurol Neurophysiol, 10(488), 2.
Iqbal, A., & Syed, A. O. (n.d.). Clay County edition Unveiling the Mystery: A Comprehensive Guide to Understanding Epilepsy.
Nafea, M. S., & Ismail, Z. H. (2022). Supervised machine learning and deep learning techniques for epileptic seizure recognition using EEG signals—A systematic literature review. Bioengineering, 9(12), 781.
Nair, P. P., Aghoram, R., & Khilari, M. L. (2021). Applications of artificial intelligence in epilepsy. International Journal of Advanced Medical and Health Research, 8(2), 41–48.
Novak, A., Vizjak, K., & Rakusa, M. (2022). Cognitive Impairment in People with Epilepsy. Journal of Clinical Medicine, 11(1), 267. https://doi.org/10.3390/jcm11010267
Williams, C., & Nutbrown, D. L. (2021). A Review of Research into the Health Benefits of Cannabidiol (CBD). The Neighborhood Academy: Pittsburgh, PA, USA.
World Health Organization. (2024). Epilepsy. World Health Organization (WHO). https://www.who.int/news-room/fact-sheets/detail/epilepsy
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