Neurodegenerative diseases encompass a group of conditions characterized by the progressive degeneration and death of nerve cells, which include disorders like Parkinson's disease, Alzheimer's disease, and several other severe neurological conditions. Widespread neuron loss due to apoptosis or aberrant protein aggregates are common pathological features. To date, treatments remain largely symptomatic, offering only temporary relief without halting disease progression. Traditional diagnostic methods heavily depend on clinical signs appearing at advanced disease stages, often too late for optimal therapeutic intervention, underlying the urgent need for innovative, objective diagnostic and prognostic approaches.
This Research Topic aims to spotlight the recent advancements and clinical applications of Artificial Intelligence (AI) in addressing neurodegenerative diseases. The focus is on narrowing the existing gap between AI technologies and practical clinical applications, thereby enhancing early diagnostic accuracy and improving prognostic evaluations to enable timely and effective clinical interventions.
To gather further insights into the application of AI in this domain, we welcome articles addressing, but not limited to, the following themes:
• AI in early detection, diagnosis, and prognostic prediction of neurodegenerative diseases.
• Personalized treatment plans for neurodegenerative conditions using artificial intelligence.
• Integration of AI with modern imaging technologies (MRI, CT, US) for studying neurodegenerative diseases.
• Exploration of risk factors and causal relationships in neurodegenerative diseases through AI.
• Novel approaches in radiomics, deep learning, and machine learning for neurological research.
We also encourage submissions across various types of articles recognized by Frontiers in Neurology, aiming to enhance the body of knowledge on cognitive impairment and motor dysfunction across a spectrum of neurodegenerative conditions.
Neurodegenerative diseases encompass a group of conditions characterized by the progressive degeneration and death of nerve cells, which include disorders like Parkinson's disease, Alzheimer's disease, and several other severe neurological conditions. Widespread neuron loss due to apoptosis or aberrant protein aggregates are common pathological features. To date, treatments remain largely symptomatic, offering only temporary relief without halting disease progression. Traditional diagnostic methods heavily depend on clinical signs appearing at advanced disease stages, often too late for optimal therapeutic intervention, underlying the urgent need for innovative, objective diagnostic and prognostic approaches.
This Research Topic aims to spotlight the recent advancements and clinical applications of Artificial Intelligence (AI) in addressing neurodegenerative diseases. The focus is on narrowing the existing gap between AI technologies and practical clinical applications, thereby enhancing early diagnostic accuracy and improving prognostic evaluations to enable timely and effective clinical interventions.
To gather further insights into the application of AI in this domain, we welcome articles addressing, but not limited to, the following themes:
• AI in early detection, diagnosis, and prognostic prediction of neurodegenerative diseases.
• Personalized treatment plans for neurodegenerative conditions using artificial intelligence.
• Integration of AI with modern imaging technologies (MRI, CT, US) for studying neurodegenerative diseases.
• Exploration of risk factors and causal relationships in neurodegenerative diseases through AI.
• Novel approaches in radiomics, deep learning, and machine learning for neurological research.
We also encourage submissions across various types of articles recognized by Frontiers in Neurology, aiming to enhance the body of knowledge on cognitive impairment and motor dysfunction across a spectrum of neurodegenerative conditions.