{"id":"https://openalex.org/W7127051058","doi":"https://doi.org/10.32657/10356/205534","title":"Self- and semi-supervised machine learning techniques for discovering novel ocular and neuroimaging biomarkers of Alzheimer's disease","display_name":"Self- and semi-supervised machine learning techniques for discovering novel ocular and neuroimaging biomarkers of Alzheimer's disease","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7127051058","doi":"https://doi.org/10.32657/10356/205534"},"language":"en","primary_location":{"id":"doi:10.32657/10356/205534","doi":"https://doi.org/10.32657/10356/205534","is_oa":false,"landing_page_url":"https://doi.org/10.32657/10356/205534","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nanyang Technological University","raw_type":"dissertation"},"parent_works":[],"lineage":["https://openalex.org/W7127051058"],"child_works_count":0,"type":"dissertation","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/10356/205534","any_repository_has_fulltext":true},"authorships":[{"author_position":"last","author":{"id":"https://openalex.org/A5032149445","display_name":"Charlene Z. L. Ong","orcid":"https://orcid.org/0000-0003-0250-0415","observed_orcids":["https://orcid.org/0000-0003-0250-0415"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Charlene Zhi Lin Ong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.8554999828338623,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.8554999828338623,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.12939999997615814,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/alzheimer-s-disease","display_name":"Alzheimer's disease","score":0.9829999804496765},{"id":"https://openalex.org/keywords/retinal-imaging-biomarkers","display_name":"retinal imaging biomarkers","score":0.7929999828338623},{"id":"https://openalex.org/keywords/neuroimaging-biomarkers","display_name":"neuroimaging biomarkers","score":0.8700000047683716},{"id":"https://openalex.org/keywords/self-supervised-learning","display_name":"self-supervised learning","score":0.9559999704360962},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"semi-supervised learning","score":0.9980000257492065},{"id":"https://openalex.org/keywords/retinal-layer-segmentation","display_name":"retinal layer segmentation","score":0.9769999980926514},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.8500000238418579},{"id":"https://openalex.org/keywords/masked-autoencoder","display_name":"masked autoencoder","score":0.8320000171661377},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.9639999866485596},{"id":"https://openalex.org/keywords/dementia-diagnosis","display_name":"dementia diagnosis","score":0.3700000047683716},{"id":"https://openalex.org/keywords/retinal-thickness","display_name":"retinal thickness","score":0.47999998927116394},{"id":"https://openalex.org/keywords/mri-biomarkers","display_name":"MRI biomarkers","score":0.3610000014305115},{"id":"https://openalex.org/keywords/robustness-to-noisy-data","display_name":"noisy data robustness","score":0.4950000047683716}],"concepts":[{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.7333999872207642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995999813079834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.694599986076355},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.6255000233650208},{"id":"https://openalex.org/C2781197716","wikidata":"https://www.wikidata.org/wiki/Q864574","display_name":"Biomarker","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5339999794960022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5038999915122986},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4530999958515167},{"id":"https://openalex.org/C124535831","wikidata":"https://www.wikidata.org/wiki/Q4915074","display_name":"Biomarker discovery","level":4,"score":0.4219000041484833},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.3043999969959259},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.26489999890327454},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C2779483572","wikidata":"https://www.wikidata.org/wiki/Q83030","display_name":"Dementia","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.32657/10356/205534","doi":"https://doi.org/10.32657/10356/205534","is_oa":false,"landing_page_url":"https://doi.org/10.32657/10356/205534","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nanyang Technological University","raw_type":"dissertation"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/205534","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/10356/205534","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis-Doctor of Philosophy"}],"best_oa_location":{"id":"pmh:oai:dr.ntu.edu.sg:10356/205534","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/10356/205534","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis-Doctor of Philosophy"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8560000061988831,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4396578660","https://openalex.org/W6964393114","https://openalex.org/W7125687431","https://openalex.org/W4386352627","https://openalex.org/W4409965380","https://openalex.org/W3046758212","https://openalex.org/W7116880861","https://openalex.org/W7162878478","https://openalex.org/W7166543232","https://openalex.org/W2952258391"],"abstract_inverted_index":{"There":[0],"is":[1,83,139,268,273,377,391,550],"increasing":[2],"prevalence":[3],"of":[4,12,58,89,113,143,152,158,174,205,229,254,256,331,387,440,514,533,546,558,591,609,621,635,652,660,669,678,706,716,726],"Alzheimer\u2019s":[5,13,42,77,300,524,562,625,682,717,739],"disease":[6,24,78,210,525,626,683],"worldwide.":[7],"To":[8,564],"manage":[9],"the":[10,23,56,70,98,114,150,160,172,199,252,277,385,438,451,455,459,475,507,512,531,571,589,607,619,633,647,676,704,712,724],"progression":[11],"disease,":[14,43],"biomarkers":[15,31,48,53,75,118,129,223,405,516,519,680,710,737],"can":[16],"be":[17,286,400],"utilized":[18],"to":[19,36,76,166,261,285,315,345,393,402,410,427,449,467,540,581,588,600,692,711],"identify":[20],"patients":[21,90],"with":[22,41,350,560,570,632],"or":[25,176,193,342,728],"predict":[26],"subsequent":[27],"progression.":[28,684],"While":[29,302],"neuroimaging":[30,184,404,436,538,593,603,671,709,736],"have":[32,133,304,645],"been":[33,134,283,305],"long":[34],"established":[35,592],"visualize":[37],"structural":[38],"changes":[39,62],"associated":[40,569],"there":[44,82,138,303],"are":[45,64,243],"other":[46,346],"promising":[47,630],"such":[49,207,434,484],"as":[50,208,406,435,485,503,517],"retinal":[51,73,265,278,654],"imaging":[52,74,390],"which":[54,130,242,281,309,689],"offer":[55,106,124],"possibility":[57,532],"detecting":[59],"early":[60],"pathophysiological":[61],"and":[63,66,81,119,180,185,212,239,295,364,431,462,497,537,627,673,708,714,735],"non-invasive":[65],"widely":[67],"available.":[68],"Nevertheless,":[69],"link":[71,115],"between":[72,116],"remains":[79],"unclear":[80],"much":[84,107],"difficulty":[85],"in":[86,93,102,162,224,245,369,384,414,454,523,552,624,641,696],"procuring":[87],"datasets":[88],"for":[91,109,126,248,264,275,291,299,333,437,506,520,618,664,681,731,738],"investigation,":[92],"particular":[94],"longitudinal":[95],"datasets.":[96],"At":[97],"same":[99],"time,":[100],"advances":[101],"deep":[103,153,318],"learning":[104,122,127,154,178,195,218,319,324,577,730],"also":[105,356,701],"promise":[108],"furthering":[110],"our":[111,338,358,699,720],"understanding":[112],"ophthalmic":[117,186,515,536,572,679,707],"dementia.":[120],"Self-supervised":[121],"techniques":[123,219],"potential":[125,297,725],"new":[128],"might":[131],"not":[132],"defined":[135],"previously.":[136],"However,":[137],"often":[140],"a":[141,203,225,287,296,317,327,407,415,422,445,553,613],"lack":[142,255],"sufficient":[144,257],"ground":[145,258],"truth":[146,259],"annotations,":[147],"hence":[148,399],"hampering":[149],"application":[151,545],"models.":[155],"In":[156,353,471,527],"light":[157],"this,":[159],"work":[161],"this":[163,246,642],"thesis":[164,700],"aims":[165],"address":[167,693],"these":[168,230,547,602,610],"issues":[169],"by":[170,473],"exploring":[171],"use":[173],"self":[175,192],"semi-supervised":[177,194,653,687,729],"approaches":[179,307,688],"leveraging":[181],"on":[182,202,380],"both":[183,429,535],"imaging.":[187],"By":[188],"utilizing":[189],"unlabeled":[190],"datasets,":[191,698],"could":[196,220,690],"potentially":[197],"improve":[198],"model":[200,617],"performance":[201,344],"range":[204],"tasks,":[206],"segmentation,":[209],"classification,":[211],"prognosis":[213,715],"prediction.":[214],"More":[215],"importantly,":[216],"self-supervised":[217,576],"uncover":[221],"novel":[222,733],"data-driven":[226],"manner.":[227],"Some":[228],"methods":[231],"include":[232],"generative":[233,322],"adversarial":[234,323],"networks,":[235,238],"graph":[236,423,614],"neural":[237,425],"masked":[240,579],"autoencoders,":[241],"explored":[244],"study":[247],"biomarker":[249,290,298],"discovery.":[250],"Firstly,":[251],"challenge":[253],"annotation":[260,311,694],"develop":[262,316],"models":[263],"layer":[266,271,279,655],"segmentation":[267,272,656],"investigated.":[269],"Retinal":[270],"critical":[274],"quantifying":[276],"thickness,":[280,496],"has":[282],"shown":[284],"useful":[288],"diagnostic":[289],"age-related":[292],"macular":[293],"degeneration":[294],"disease.":[301,563,718,740],"existing":[306,468],"developed":[308],"reduce":[310],"need,":[312],"we":[313,355,510,529,574,595,644,722],"propose":[314],"approach":[320,339,359,420,663],"using":[321,612],"that":[325,337],"utilizes":[326],"very":[328],"limited":[329,351],"number":[330],"labels":[332],"segmentation.":[334],"We":[335,605],"demonstrated":[336],"showed":[340,365,628],"comparable":[341],"superior":[343],"state-of-the-art":[347,469],"approaches,":[348],"particularly":[349],"labels.":[352],"addition,":[354,472],"evaluated":[357],"under":[360],"various":[361],"noisy":[362,371],"conditions":[363],"it":[366],"was":[367],"robust":[368],"most":[370],"conditions.":[372],"Secondly,":[373],"current":[374],"dementia":[375],"diagnosis":[376,713],"based":[378],"primarily":[379],"clinical":[381,411,430,554],"assessment.":[382],"Neuroimaging":[383],"form":[386,541],"magnetic":[388],"resonance":[389],"used":[392],"provide":[394],"additional":[395],"granularity.":[396],"It":[397,443],"will":[398],"practical":[401],"explore":[403,511,530],"value":[408,705],"add":[409],"assessment,":[412],"especially":[413],"pre-dementia":[416],"cohort.":[417],"Our":[418],"proposed":[419],"uses":[421],"convolutional":[424,615],"network":[426,616],"combine":[428],"non-clinical":[432,456],"features":[433,453,505,539,549,611],"classification":[439,662],"cognitive":[441,521,622,665],"syndromes.":[442],"integrates":[444],"Cross":[446],"Attention":[447],"Module":[448],"highlight":[450],"salient":[452],"features,":[457,483],"attaining":[458],"highest":[460],"accuracy":[461],"Matthew\u2019s":[463],"correlation":[464],"coefficient":[465],"compared":[466],"methods.":[470],"investigating":[474,675],"feature":[476,567,583],"interpretability":[477],"via":[478,578],"Integrated":[479],"Gradients,":[480],"several":[481],"nonclinical":[482],"cerebrospinal":[486],"fluid":[487],"volume,":[488,492],"right":[489,493],"hippocampal":[490],"fissure":[491],"frontal":[494],"pole":[495],"left":[498],"pallidum":[499],"volume":[500],"were":[501],"identified":[502],"key":[504,566,670],"classification.":[508],"Thirdly,":[509],"utility":[513],"prognostic":[518],"decline":[522,623],"patients.":[526],"parallel,":[528],"combining":[534],"multimodal":[542,548,661],"features.":[543,604],"The":[544],"investigated":[551,606],"trial":[555],"dataset":[556],"consisting":[557],"participants":[559],"mild-to-moderate":[561],"learn":[565],"representations":[568],"images,":[573],"utilize":[575,596],"autoencoders":[580],"extract":[582],"representations.":[584],"For":[585],"neuroimaging,":[586],"due":[587],"availability":[590],"software,":[594],"standard":[597],"preprocessing":[598],"pipelines":[599],"obtain":[601],"combination":[608],"prediction":[620],"initial":[629],"results":[631],"addition":[634],"optical":[636],"coherence":[637],"tomography":[638],"data.":[639],"Overall,":[640],"thesis,":[643],"made":[646],"following":[648],"contributions:":[649],"(1)":[650],"development":[651,659],"approach,":[657],"(2)":[658],"syndromes,":[666],"(3)":[667],"elucidation":[668],"biomarkers,":[672],"(4)":[674],"relevance":[677],"Beyond":[685],"building":[686],"help":[691],"scarcity":[695],"medical":[697],"further":[702],"clarifies":[703],"Through":[719],"study,":[721],"demonstrate":[723],"self-":[727],"discovering":[732],"ocular":[734]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-02-03T00:00:00"}