AI-Driven Integration of Multimodal Imaging and Clinical Data for Long COVID: Mapping Brain-Behavior Associations and Treatment Outcomes
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 1330
Special Issue Editors
Interests: neurophysiology; cannabis; non-invasive brain stimulation; neuroimaging; fatigue
Special Issues, Collections and Topics in MDPI journals
Interests: PET imaging; imaging instrumentation; artificial intelligence; machine learning; image segmentation; modeling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The emergence of Long COVID has fundamentally challenged our healthcare systems, with an estimated 10–30% of COVID-19 survivors experiencing persistent symptoms across multiple organ systems, including significant neurological manifestations such as brain fog, memory deficits, and cognitive dysfunction. This complex syndrome, which has been linked to neuroinflammation and disrupted neural circuitry, demands sophisticated approaches for accurate diagnosis, prognosis, and treatment optimization. While early research relied on single-modality imaging and conventional analyses, the field has rapidly evolved toward more integrated approaches that leverage artificial intelligence.
Recent technological advances have created unprecedented opportunities to transform Long COVID care. The convergence of sophisticated deep learning architectures, high-quality multimodal imaging, and enhanced clinical informatics now enables comprehensive patient assessments, including detailed mapping of neural connectivity patterns and cognitive performance metrics. These developments allow for the simultaneous analysis of multiple imaging modalities (MRI, CT, PET, ultrasound), clinical measurements, biomarkers, longitudinal health records, and neurocognitive testing results.
This Special Issue focuses on innovative approaches to integrating artificial intelligence with multimodal imaging and clinical data in Long COVID research, with particular emphasis on neurocognitive outcomes. We seek submissions that advance automated diagnosis, disease trajectory prediction, treatment response optimization, and patient stratification. Of particular interest are studies that demonstrate practical clinical applications, novel AI architectures for heterogeneous data integration, and investigations into the neurobiological mechanisms underlying persistent symptoms.
By bringing together cutting-edge research in this rapidly evolving field, we aim to accelerate the development of more-effective and personalized approaches to Long COVID care, especially in addressing its neurological and psychiatric manifestations. This Special Issue welcomes original research articles, comprehensive reviews, and perspective pieces that showcase the successful integration of multiple data streams and AI-driven approaches to improve patient outcomes.
Dr. Thorsten Rudroff
Dr. Riku Klén
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- neuroinflammation
- cognitive dysfunction
- multimodal imaging
- neural connectivity
- deep learning
- neurocognitive assessment
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