11 results for "Michael Lassi"
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Journal Article
Post-stroke spontaneous motor recovery in mice can be predicted from acute-phase local field potential using machine learning
Stroke remains a leading cause of long-term disability, underscoring the urgent need for effective predictors of motor recovery. Understanding the electrophysiological changes underlying spontaneous recovery could offer critical insight into recovery mechanisms and aid in predicting individual…
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Journal Article
A multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data – A pilot-study
Abstract Background Forecasting post-stroke rehabilitation outcome is essential to personalize therapeutic strategies. Traditional approaches rely on clinical assessment scales, which, while essential, may benefit from complementary objective measures. In this direction, robot-assisted assessment…
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Journal Article
Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients
Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) methods have long been used for exploring brain…
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Journal Article
Digital twins support cross-modal and cross-centric classification of mild cognitive impairment
Abstract Background Neural recordings capture crucial pathophysiological processes along the dementia continuum. However, cross-center variability in recording techniques and paradigms limit their generalizability and diagnostic power, preventing clinical use. We here propose a computational…
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Journal Article
EEG recordings during visuo‐attentive task reduce sex bias in Alzheimer's disease diagnosis
Abstract INTRODUCTION Pathological cognitive decline affects roughly 15% of older adults, presenting relevant sex differences, being a stronger predictor of Alzheimer's disease in females. Yet, sex‐specific neural markers that support a balanced early diagnosis remain limited. Event‐related…
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Journal Article Full text
Enhancing upper limb motor recovery prediction after acute stroke using EEG and subacute data
Electroencephalography (EEG) has shown promise in assessing and monitoring functional recovery in stroke survivors, but its utility in predicting upper limb motor recovery in a data-driven framework remains underexplored. This study presents a novel EEG-based machine-learning model, StrokeRecovNet…
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Journal Article
Personalized modeling of Alzheimer's disease progression estimates neurodegeneration severity from EEG recordings
Abstract INTRODUCTION Early identification of Alzheimer's disease (AD) is necessary for a timely onset of therapeutic care. However, cortical structural alterations associated with AD are difficult to discern. METHODS We developed a cortical model of AD‐related neurodegeneration accounting for…
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Journal Article
Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer’s Disease continuum?
Alzheimer’s disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the…
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Journal Article
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer’s Disease With machine learning: the PREVIEW study protocol
Abstract Background As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest stages of the disease. Subjective Cognitive Decline (SCD) is a condition in…
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Journal Article
Digital twins and non-invasive recordings enable early diagnosis of Alzheimer’s disease
Abstract Background The diagnosis of Alzheimer’s disease (AD) in its preclinical stages, such as subjective cognitive decline (SCD), is crucial for a timely management of the condition. However, current early diagnostic methods are unsuitable for preclinical screenings due to limited availability…
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Journal Article
Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration
Abstract Cognitive decline is a condition affecting almost one sixth of the elder population and is widely regarded as one of the first manifestations of Alzheimer’s disease. Despite the extensive body of knowledge on the condition, there is no clear consensus on the structural defects and…