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EMG Graphof Parkinson's DiseasePatient
+is+a+debilitating+neurodegenerative+disease+that+has+severe+impacts+on+an+individual%27s+quality+of+life.+Compared+with+structural+and+functional+MRI-based+biomarkers+for+the+disease%252C+electroencephalography+(EEG)+can+provide+more+accessible+alternatives+for+clinical+insights.+While+deep+learning+(DL)+techniques+have+provided+excellent+outcomes%252C+many+techniques+fail+to+model+spatial+information+and+dynamic+brain+connectivity%252C+and+face+challenges+in+robust+feature+learning%252C+limited+data+sizes%252C+and+poor+explainability.+To+address+these+issues%252C+we+proposed+a+novel+graph+neural+network+(GNN)+technique+for+explainable+PD+detection+using+resting+state+EEG.+Specifically%252C+we+employ+structured+global+convolutions+with+contrastive+learning+to+better+model+complex+features+with+limited+data%252C+a+novel+multi-head+graph+structure+learner+to+capture+the+non-Euclidean+structure+of+EEG+data%252C+and+a+head-wise+gradient-weighted+graph+attention+explainer+to+offer+neural+connectivity+insights.+We+developed+and+evaluated+our+method+using+the+UC+San+Diego+Parkinson%27s+disease+EEG+dataset%252C+and+achieved+69.40%2525+detection+accuracy+in+subject-wise+leave-one-out+cross-validation+while+generating+intuitive+explanations+for+the+learnt+graph+topology.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.a80b1917be185ff0e87dce23403d5c02%3frik%3dbcmr2ruBNcTe%252fQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=EMG+Graph+of+Parkinson%27s+Disease+Patient&FORM=IRPRST&ck=708CC8126F8B419AA88C5CFB7E393AE4&selectedIndex=28&itb=0)
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