{"doi":"10.1371/journal.pone.0288039","title":"Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach","abstract":"INTRODUCTION: The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data. METHODS: 927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database. RESULTS: Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal. DISCUSSION: Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.","journal":"PLoS ONE","year":2023,"id":366262,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7171,"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":1122503,"name":"Evgeniy Marinov","orcid":"0000-0002-9684-9142","position":1,"is_corresponding":false},{"id":996502,"name":"Simon Young","orcid":"0000-0002-8835-7164","position":2,"is_corresponding":false},{"id":1074023,"name":"Sophia Lazarova","orcid":"0000-0003-0349-5769","position":3,"is_corresponding":false},{"id":1074024,"name":"Деница Григорова","orcid":"0000-0002-8426-0576","position":4,"is_corresponding":false},{"id":1122504,"name":"Dean Palejev","orcid":"0000-0002-0563-6636","position":5,"is_corresponding":false},{"id":395841,"name":"Ivan Koychev","orcid":"0000-0001-6813-8493","position":0,"is_corresponding":true}],"reference_count":52,"raw_metadata":null,"created_at":"2026-07-19T01:14:55.198227Z","pmid":"37856502","pmcid":null,"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":[]}