{"doi":"10.1109/bibm49941.2020.9313310","title":"Learning Semi-Supervised Representation Enrichment Using Longitudinal Imaging-Genetic Data","abstract":null,"journal":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","year":2020,"id":610863,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1570732,"name":"Lodewijk Brand","orcid":null,"position":1,"is_corresponding":false},{"id":868721,"name":"Hua Wang","orcid":"0000-0003-2633-3420","position":2,"is_corresponding":false},{"id":1570731,"name":"Hoon Seo","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Learning Semi-Supervised Representation Enrichment Using Longitudinal Imaging-Genetic Data","abstract":"Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Recently, many statistical learning methods have been presented to predict cognitive declines by using longitudinal imaging data. However, missing records that broadly exist in the longitudinal neuroimaging data have posed a critical challenge for effectively using these data in machine learning models. To tackle this difficulty, in this paper we propose a novel approach to integrate longitudinal (dynamic) phenotypic data and static genetic data to learn a fixed-length biomarker representation using the enrichment learned from the temporal data in multiple imaging modalities. Armed with this enriched biomarker representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD. We have applied our new method on the Alzheimer's Disease Neruoimaging Initiative (ADNI) cohort and achieved promising experimental results that validate its effectiveness.","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"23304386","pmcid":null,"openalex_id":"https://openalex.org/W3127037167","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.19141124,"influential_citations":0,"citation_trend":[{"year":2024,"count":1}],"oa_status":"closed","license":"https://doi.org/10.15223/policy-029","oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx7/9312958/9312977/09313310.pdf?arnumber=9313310","host_type":"publisher"},{"url":"https://doi.org/10.1109/bibm49941.2020.9313310","host_type":""}],"fields_of_study":["Machine Learning in Healthcare","Dementia and Cognitive Impairment Research","Statistical Methods and Inference"],"mesh_terms":[],"keywords":["Computer science","Neuroimaging","Artificial intelligence","Missing data","Machine learning","Alzheimer's Disease Neuroimaging Initiative","Cognition","External Data Representation","Feature learning","Modalities","Representation (politics)","Genetic data","Deep learning","Data modeling","Pattern recognition (psychology)","Psychology","Neuroscience","Cognitive impairment","Medicine"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-01T12:08:31.374506Z","pmid":null,"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":[]}