Towards Transforming Neurorehabilitation: The Impact of Artificial Intelligence on Diagnosis and Treatment of Neurological Disorders

Biomedicines, Journal Year: 2024, Volume and Issue: 12(10), P. 2415 - 2415

Published: Oct. 21, 2024

Background and Objectives: Neurological disorders like stroke, spinal cord injury (SCI), Parkinson’s disease (PD) significantly affect global health, requiring accurate diagnosis long-term neurorehabilitation. Artificial intelligence (AI), such as machine learning (ML), may enhance early diagnosis, personalize treatment, optimize rehabilitation through predictive analytics, robotic systems, brain-computer interfaces, improving outcomes for patients. This systematic review examines how AI ML systems influence treatment in neurorehabilitation among neurological disorders. Materials Methods: Studies were identified from an online search of PubMed, Web Science, Scopus databases with a time range 2014 to 2024. has been registered on Open OSF (n) EH9PT. Results: Recent advancements are revolutionizing motor conditions SCI, PD, offering new opportunities personalized care improved outcomes. These technologies clinical assessments, therapy personalization, remote monitoring, providing more precise interventions better management. Conclusions: is neurorehabilitation, personalized, data-driven treatments that recovery Future efforts should focus large-scale validation, ethical considerations, expanding access advanced, home-based care.

Language: Английский

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Research Progress of Flavonoids in Spinal Cord Injury: Therapeutic Mechanisms and Drug Delivery Strategies

Phytotherapy Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Spinal cord injury (SCI) is a serious neurological disease with an extremely high disability rate. Most patients show loss of motor and sensory functions below the level injury. Current treatment protocols are based on early surgical decompression pharmacotherapy. However, efficacy these interventions suboptimal. Due to its complex pathophysiological mechanisms difficulty central nervous system (CNS) regeneration, exploring effective therapeutic remains daunting. Flavonoids secondary metabolites unique plants that have attracted attention in recent years for their potential now commonly used inflammation, tumors, other diseases. For SCI, related studies still exploring; some compounds, such as quercetin, fisetin, hesperetin, shown good anti-inflammatory anti-apoptotic properties, which help restore function injured spinal cord. flavonoids exhibit certain disadvantages, including poor solubility, low bioavailability, inability achieve long-term controlled release. Some proposed drug delivery strategies-including nanoparticles, hydrogels, collagen scaffolds-to enhance efficacy. In this paper, we summarize strategies SCI by searching relevant literature propose future research directions provide new ideas multimodal SCI.

Language: Английский

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Harnessing Artificial Neural Networks for Spinal Cord Injury Prognosis

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(15), P. 4503 - 4503

Published: Aug. 1, 2024

Background: Prediction of neurorehabilitation outcomes after a Spinal Cord Injury (SCI) is crucial for healthcare resource management and improving prognosis rehabilitation strategies. Artificial neural networks (ANNs) have emerged as promising alternative to conventional statistical approaches identifying complex prognostic factors in SCI patients. Materials: database 1256 patients admitted was analyzed. Clinical demographic data characteristics were used predict functional using both ANN linear regression models. The former structured with input, hidden, output layers, while the identified significant variables affecting outcomes. Both aimed evaluate compare their accuracy measured by Independence Measure (SCIM) score. Results: models key predictors outcomes, such age, injury level, initial SCIM scores (correlation actual outcome: R = 0.75 0.73, respectively). When also alimented parameters recorded during hospitalization, highlighted importance these additional factors, like motor completeness complications showing an improvement its (R 0.87). Conclusions: seemed be not widely superior classical statistics general, but, taking into account non-linear relationships among variables, emphasized impact hospitalization on recovery, particularly respiratory issues, deep vein thrombosis, urological complications. These results suggested that recovery

Language: Английский

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Using Artificial Intelligence in the Comprehensive Management of Spinal Cord Injury

Korean Journal of Neurotrauma, Journal Year: 2024, Volume and Issue: 20(4), P. 215 - 215

Published: Jan. 1, 2024

Spinal cord injury (SCI) frequently results in persistent motor, sensory, or autonomic dysfunction, and the outcomes are largely determined by location severity of injury. Despite significant technological progress, intricate nature spinal anatomy difficulties associated with neuroregeneration make full recovery from SCI uncommon. This review explores potential artificial intelligence (AI), a particular focus on machine learning, to enhance patient management. The application AI, specifically has revolutionized diagnosis, treatment, prognosis, rehabilitation patients SCI. By leveraging large datasets identifying complex patterns, AI contributes improved diagnostic accuracy, optimizes surgical procedures, enables personalization therapeutic interventions. AI-driven prognostic models provide accurate predictions recovery, facilitating planning resource allocation. Additionally, AI-powered systems, including robotic devices brain-computer interfaces, increase effectiveness accessibility therapy. However, realizing care requires ongoing research, interdisciplinary collaboration, development comprehensive datasets. As continues evolve, it is expected play an increasingly vital role enhancing

Language: Английский

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