Artificial Intelligence in Early Detection of Neurological Disorders
Abstract
Because the start of neurological illnesses is sometimes subtle and gradual, early detection has always been a difficult task in the field of medical diagnostics. In addition to impeding prompt intervention, delayed diagnosis has a substantial negative influence on long-term results and patient quality of life. The development of artificial intelligence (AI) and machine learning (ML) in recent years has created revolutionary possibilities to raise the precision, effectiveness, and predictive capacity of neurological evaluations. This study offers a thorough analysis of the development, status, and prospects of AI-driven approaches in neurological diagnosis. We look at the creation of AI algorithms that can analyze massive clinical, genomic, and neuroimaging information and find patterns that are invisible to the human eye. Their use in the diagnosis of epilepsy, multiple sclerosis, Parkinson's disease, and Alzheimer's disease is specifically highlighted. These models exhibit improved capacities in disease classification, progression tracking, and early-stage identification.The study also discusses the incorporation of AI into healthcare workflows, showcasing both successful case studies and persistent issues such data heterogeneity, black-box model interpretability, and regulatory validation requirements. The significance of implementing AI in healthcare responsibly is emphasized by the ethical issues raised by algorithmic bias, data privacy, and patient permission.Lastly,…
Read the paper
Related studies
- Improving the translation of search strategies using the Polyglot Search Translator: a randomized controlled trial
- Nutritional, Physical, Cognitive, and Combination Interventions and Frailty Reversal Among Older Adults: A Randomized Controlled Trial
- Clinical characteristics and risk factors associated with COVID-19 severity in patients with haematological malignancies in Italy: a retrospective, multicentre, cohort study
- A randomized, controlled trial of oral propranolol in infantile hemangioma
- Clinical phenotypes of delirium during critical illness and severity of subsequent long-term cognitive impairment: a prospective cohort study
- Increased physical activity improves sleep and mood outcomes in inactive people with insomnia: a randomized controlled trial
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.