{"doi":"10.1002/alz.13411","title":"Novel methodology for detection and prediction of mild cognitive impairment using resting‐state EEG","abstract":"BACKGROUND: Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency. METHODS: Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score. RESULTS: The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%. CONCLUSION: The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.","journal":"Alzheimer s & Dementia","year":2023,"id":328348,"datarank":0.6836649104721636,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"self_citation_contribution":0.47670807455219194,"citation_network_contribution":0.20695683591997163,"self_endowment_contribution":0.47670807455219194,"citer_contribution":0.20695683591997163,"corpus_percentile":70.81302699775664,"corpus_rank":3774,"citation_count":23,"citer_count":19,"citers_with_citation_signal":12,"citers_with_endowment":12,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7943,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1049780,"name":"Boxin Sun","orcid":"0009-0007-9411-9975","position":1,"is_corresponding":false},{"id":505075,"name":"Voyko Kavcic","orcid":"0000-0002-3874-3892","position":2,"is_corresponding":false},{"id":984662,"name":"Mingyan Liu","orcid":"0000-0003-3295-9200","position":3,"is_corresponding":false},{"id":325845,"name":"Bruno Giordani","orcid":"0000-0001-5921-3455","position":4,"is_corresponding":false},{"id":1049781,"name":"Tongtong Li","orcid":"0000-0001-7506-5368","position":5,"is_corresponding":false},{"id":1049779,"name":"Jinxian Deng","orcid":"0009-0000-5517-1075","position":0,"is_corresponding":true}],"reference_count":68,"raw_metadata":null,"created_at":"2026-07-19T01:08:52.196069Z","pmid":"37496373","pmcid":"PMC10811294","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}