{"doi":"10.48550/arxiv.2011.06531","title":"Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design","abstract":"Alzheimer's disease (AD) is associated with local (e.g. brain tissue atrophy) and global brain changes (loss of cerebral connectivity), which can be detected by high-resolution structural magnetic resonance imaging. Conventionally, these changes and their relation to AD are investigated independently. Here, we introduce a novel, highly-scalable approach that simultaneously captures $\\textit{local}$ and $\\textit{global}$ changes in the diseased brain. It is based on a neural network architecture that combines patch-based, high-resolution 3D-CNNs with global topological features, evaluating multi-scale brain tissue connectivity. Our local-global approach reached competitive results with an average precision score of $0.95\\pm0.03$ for the classification of cognitively normal subjects and AD patients (prevalence $\\approx 55\\%$).","journal":"arXiv (Cornell University)","year":2020,"id":123124,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9553,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":566512,"name":"Felix Hensel","orcid":null,"position":1,"is_corresponding":false},{"id":565759,"name":"Catherine R. Jutzeler","orcid":"0000-0001-7167-8271","position":2,"is_corresponding":false},{"id":565760,"name":"Bastian Rieck","orcid":"0000-0003-4335-0302","position":3,"is_corresponding":false},{"id":565758,"name":"Sarah C. Brüningk","orcid":"0000-0003-3176-1032","position":0,"is_corresponding":true}],"reference_count":9,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:14:59.547352Z","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":[]}