Latest AI and machine learning research in neurology for healthcare professionals.
Adult degenerative scoliosis arises after skeletal maturity in an initially normal spine, primarily driven by age-related degeneration. The Cobb angle, the angle between the most tilted vertebrae typically derived from radiographs, remains the clinical standard for assessing curvature severity, yet large-scale evaluation using MRI has not been feasible. This study developed an automated method for...
Genetic risk factors for neuropsychiatric disorders are well documented. However, some individuals with high genetic risk remain unaffected, and the mechanisms underlying such resilience remain poorly understood. The presence of protective resilience factors that mitigate risk could help explain the disconnect between predicted risk and reality, particularly when genetic contributions are substant...
Interpretable scoring system can contribute to bridge the gap between the timeliness and complexity of diagnosing Alzheimer’s disease (AD) and promote...
Major depressive disorder (MDD) with suicidality represents a significant public health concern, as suicide ranks among the leading causes of death wo...
Early identification of dementia risk is essential for preventive care and timely enrolment into disease-modifying interventions. Current approaches r...
There is need to detect and intervene in pre-clinical phases of Alzheimer’s disease (AD). Electronic health records (EHRs) may help predict AD using m...
Alzheimers disease (AD) remains a major global health challenge, with growing evidence linking chronic infections, immune aging, and neurodegeneration...
We present a Bayesian machine learning framework integrating genetic, molecular, and wearable sensor biomarkers for precision medicine in Parkinson’s ...
Detecting schizophrenia (SZ) from electroencephalography (EEG) signals using machine- and deep learning models gained traction lately due to potential...
Can self-supervised speech foundation models (SFMs) be used for automatic patient metadata extraction, even when no prior demographic information is a...
Alzheimer’s disease (AD) genome-wide association studies (GWAS), typically based on clinical phenotypes, have identified numerous risk loci, yet linki...
Ventriculomegaly is a key neuroimaging feature in conditions such as normal pressure hydrocephalus (NPH) and other disorders of cerebrospinal fluid (C...
Blood-based metabolomic signatures offer promising, non-invasive avenues for Alzheimer’s disease (AD) detection. We aimed to identify a serum metaboli...
Gait impairment is a characteristic motor deficit of Parkinson’s disease (PD) and a critical but insufficiently understood target of deep brain stimul...
Deviations from normative brain ageing trajectories are linked to a wide range of adverse health outcomes. A number of brain age prediction models hav...
Epilepsy affects around 50 million people worldwide and remains a major diagnostic challenge, particularly in resource-limited settings. Electroenceph...
Large language models (LLMs) offer new opportunities to synthesize the vast and heterogeneous biomedical literature, yet their potential to support dr...
Cognitive dysfunction often co-occurs with psychopathology. Advances in neuroimaging and machine learning have led to neural indicators that predict i...
Parkinson’s disease (PD) involves variable patterns of brain atrophy in different motor and cognitive regions that differ across patients in both loca...
Leg dystonia in cerebral palsy (CP) is debilitating but remains underdiagnosed. Routine clinical evaluation has only 12% accuracy for leg dystonia dia...