{"id":"https://openalex.org/W2783189612","doi":"https://doi.org/10.1109/bigdata.2017.8258139","title":"Recovering loss to followup information using denoising autoencoders","display_name":"Recovering loss to followup information using denoising autoencoders","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783189612","doi":"https://doi.org/10.1109/bigdata.2017.8258139","mag":"2783189612"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.04664","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102732934","display_name":"Lovedeep Gondara","orcid":"https://orcid.org/0000-0002-1707-8141"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]},{"id":"https://openalex.org/I1289530486","display_name":"BC Cancer Agency","ror":"https://ror.org/03sfybe47","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1289530486"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Lovedeep Gondara","raw_affiliation_strings":["British Columbia Cancer Agency","Simon Fraser University"],"affiliations":[{"raw_affiliation_string":"British Columbia Cancer Agency","institution_ids":["https://openalex.org/I1289530486"]},{"raw_affiliation_string":"Simon Fraser University","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001578135","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0003-0844-5023"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":["Simon Fraser University"],"affiliations":[{"raw_affiliation_string":"Simon Fraser University","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102732934"],"corresponding_institution_ids":["https://openalex.org/I1289530486","https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":0.739,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.8158216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1936","last_page":"1945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.6758042573928833},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6616737842559814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5738575458526611},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.49592098593711853},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34116482734680176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6758042573928833},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6616737842559814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5738575458526611},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.49592098593711853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34116482734680176}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2017.8258139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1802.04664","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.04664","pdf_url":"https://arxiv.org/pdf/1802.04664","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1802.04664","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.04664","pdf_url":"https://arxiv.org/pdf/1802.04664","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W573849129","https://openalex.org/W1528194431","https://openalex.org/W1580788756","https://openalex.org/W1665214252","https://openalex.org/W1836465849","https://openalex.org/W1951710781","https://openalex.org/W1965031889","https://openalex.org/W1973748105","https://openalex.org/W1973948212","https://openalex.org/W1976568348","https://openalex.org/W1979300931","https://openalex.org/W1982218878","https://openalex.org/W1984045048","https://openalex.org/W1994079917","https://openalex.org/W2013188809","https://openalex.org/W2025768430","https://openalex.org/W2032010130","https://openalex.org/W2038585576","https://openalex.org/W2095705004","https://openalex.org/W2096391232","https://openalex.org/W2096555119","https://openalex.org/W2097998348","https://openalex.org/W2100495367","https://openalex.org/W2115098571","https://openalex.org/W2132587081","https://openalex.org/W2133470535","https://openalex.org/W2155980444","https://openalex.org/W2167187602","https://openalex.org/W2345010043","https://openalex.org/W2404595106","https://openalex.org/W2498119267","https://openalex.org/W2508457857","https://openalex.org/W2514294276","https://openalex.org/W2550179689","https://openalex.org/W2615395371","https://openalex.org/W2795680774","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2950800384","https://openalex.org/W2953238046","https://openalex.org/W3199465508","https://openalex.org/W4293241248","https://openalex.org/W4298826872","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6674330103","https://openalex.org/W6674385629","https://openalex.org/W6679352395","https://openalex.org/W6679695472","https://openalex.org/W6714138976","https://openalex.org/W6738025973"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Loss":[0],"to":[1,26,37,57,60,64,88],"followup":[2,27,61,89],"is":[3,81],"a":[4,14,50,97],"significant":[5],"issue":[6],"in":[7,102],"healthcare":[8],"and":[9,17,35,42,74,86,91],"has":[10],"serious":[11],"consequences":[12],"for":[13,23,110],"study's":[15],"validity":[16],"cost.":[18],"Methods":[19],"available":[20],"at":[21],"present":[22],"recovering":[24],"loss":[25,59,87],"information":[28],"are":[29],"restricted":[30],"by":[31,96],"their":[32],"expressive":[33],"capabilities":[34],"struggle":[36],"model":[38,51,80],"highly":[39],"non-linear":[40],"relations":[41],"complex":[43],"interactions.":[44],"In":[45],"this":[46],"paper":[47],"we":[48],"propose":[49],"based":[52],"on":[53,71],"overcomplete":[54],"denoising":[55],"autoencoders":[56],"recover":[58],"information.":[62],"Designed":[63],"work":[65],"with":[66],"high":[67],"volume":[68],"data,":[69],"results":[70],"various":[72],"simulated":[73],"real":[75],"life":[76],"datasets":[77],"show":[78],"our":[79],"appropriate":[82],"under":[83],"varying":[84],"dataset":[85,108],"conditions":[90],"outperforms":[92],"the":[93,107],"state-of-the-art":[94],"methods":[95],"wide":[98],"margin":[99],"(\u2265":[100],"20%":[101],"some":[103],"scenarios)":[104],"while":[105],"preserving":[106],"utility":[109],"final":[111],"analysis.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
