About this Research Topic
As the global population ages, the prevalence of neurodegenerative diseases is rising, posing significant challenges to healthcare systems. Artificial intelligence (AI) and radiomics are emerging as powerful tools in this domain, offering innovative methods for diagnosing, monitoring, and treating these conditions. Radiomics enables the extraction of quantitative features from medical images, while AI excels at analyzing large datasets and identifying patterns that might be imperceptible to the human eye. The integration of these technologies, particularly in neuroimaging, holds the potential to revolutionize our understanding and management of neurodegenerative diseases.
The goal of this research is to address the complex challenges posed by neurodegenerative diseases through the application of AI and radiomics. Specifically, we aim to:
1. Identify and validate novel imaging biomarkers for the early detection and monitoring of neurodegenerative disorders.
2. Develop AI-driven predictive models to assess disease progression and treatment outcomes, enabling personalized healthcare approaches.
3. Utilize machine learning and database mining techniques to analyze extensive health datasets, uncovering new insights and correlations specific to neurodegenerative diseases.
4. Evaluate the clinical utility of these technologies in enhancing diagnostic accuracy, improving patient outcomes, and optimizing healthcare resources.
Recent advances in AI algorithms, machine learning techniques, and high-throughput image analysis have made these objectives achievable. By leveraging these tools, we can develop more effective strategies for managing neurodegenerative diseases.
This Research Topic welcomes submissions that explore the application of AI and radiomics in neurodegenerative diseases. We are particularly interested in contributions that address:
- Development and validation of AI and radiomics-based biomarkers for neurodegenerative diseases.
- Neuroimaging studies utilizing AI and radiomics to understand neurodegenerative disorders.
- Machine learning models predicting disease trajectories and treatment responses in neurodegenerative conditions.
- Database mining to discover patterns in large-scale neurodegenerative health data.
We invite original research articles, reviews, case studies, and technical notes. Manuscripts should provide detailed methodologies, robust results, and a discussion of the clinical implications of the findings. Submissions must adhere to ethical standards, including patient consent and institutional review board (IRB) approvals where applicable. Join us in advancing the frontiers of neurodegenerative disease research through innovative AI and radiomics studies.
The goal of this research is to address the complex challenges posed by neurodegenerative diseases through the application of AI and radiomics. Specifically, we aim to:
1. Identify and validate novel imaging biomarkers for the early detection and monitoring of neurodegenerative disorders.
2. Develop AI-driven predictive models to assess disease progression and treatment outcomes, enabling personalized healthcare approaches.
3. Utilize machine learning and database mining techniques to analyze extensive health datasets, uncovering new insights and correlations specific to neurodegenerative diseases.
4. Evaluate the clinical utility of these technologies in enhancing diagnostic accuracy, improving patient outcomes, and optimizing healthcare resources.
Recent advances in AI algorithms, machine learning techniques, and high-throughput image analysis have made these objectives achievable. By leveraging these tools, we can develop more effective strategies for managing neurodegenerative diseases.
This Research Topic welcomes submissions that explore the application of AI and radiomics in neurodegenerative diseases. We are particularly interested in contributions that address:
- Development and validation of AI and radiomics-based biomarkers for neurodegenerative diseases.
- Neuroimaging studies utilizing AI and radiomics to understand neurodegenerative disorders.
- Machine learning models predicting disease trajectories and treatment responses in neurodegenerative conditions.
- Database mining to discover patterns in large-scale neurodegenerative health data.
We invite original research articles, reviews, case studies, and technical notes. Manuscripts should provide detailed methodologies, robust results, and a discussion of the clinical implications of the findings. Submissions must adhere to ethical standards, including patient consent and institutional review board (IRB) approvals where applicable. Join us in advancing the frontiers of neurodegenerative disease research through innovative AI and radiomics studies.
Keywords: Artificial Intelligence, Radiomics, Neurodegenerative diseases, Neuroimaging, Machine Learning, Database Mining
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
