{"id":"https://openalex.org/W2913477859","doi":"https://doi.org/10.1109/test.2018.8624884","title":"Improving Diagnosis Efficiency via Machine Learning","display_name":"Improving Diagnosis Efficiency via Machine Learning","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2913477859","doi":"https://doi.org/10.1109/test.2018.8624884","mag":"2913477859"},"language":"en","primary_location":{"id":"doi:10.1109/test.2018.8624884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/test.2018.8624884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Test Conference (ITC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103119441","display_name":"Qicheng Huang","orcid":"https://orcid.org/0000-0003-2891-6662"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qicheng Huang","raw_affiliation_strings":["Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079176809","display_name":"Chenlei Fang","orcid":"https://orcid.org/0000-0002-0518-6348"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenlei Fang","raw_affiliation_strings":["Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011949952","display_name":"Soumya Mittal","orcid":"https://orcid.org/0000-0001-8262-3313"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soumya Mittal","raw_affiliation_strings":["Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Advanced Chip Testing Laboratory (www.ece.cmu.edu/~actl/) Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039038157","display_name":"R. D. Blanton","orcid":"https://orcid.org/0000-0001-6108-2925"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. D. Blanton","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, US"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, US","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103119441"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.7772,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91249083,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6649932265281677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5842223167419434},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.578738808631897},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5529991984367371},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5392457842826843},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.528644859790802},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.48613807559013367},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4807019829750061},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4195754826068878},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3449966609477997},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.32896992564201355},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1788802146911621}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6649932265281677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5842223167419434},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.578738808631897},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5529991984367371},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5392457842826843},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.528644859790802},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.48613807559013367},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4807019829750061},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4195754826068878},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3449966609477997},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.32896992564201355},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1788802146911621},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/test.2018.8624884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/test.2018.8624884","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Test Conference (ITC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1521843029","https://openalex.org/W1564266201","https://openalex.org/W1570448133","https://openalex.org/W1594031697","https://openalex.org/W1980810142","https://openalex.org/W2031335280","https://openalex.org/W2037589385","https://openalex.org/W2055709641","https://openalex.org/W2087347434","https://openalex.org/W2119821739","https://openalex.org/W2122520060","https://openalex.org/W2131819669","https://openalex.org/W2146990954","https://openalex.org/W2148143831","https://openalex.org/W2155261478","https://openalex.org/W2159277142","https://openalex.org/W2163721513","https://openalex.org/W2167236639","https://openalex.org/W2169281690","https://openalex.org/W2186784057","https://openalex.org/W2462887203","https://openalex.org/W2521254966","https://openalex.org/W2566117353","https://openalex.org/W2571148617","https://openalex.org/W2786282599","https://openalex.org/W2911964244","https://openalex.org/W2996475963","https://openalex.org/W4212898332","https://openalex.org/W4239510810","https://openalex.org/W4297957988","https://openalex.org/W6686909317","https://openalex.org/W6719005931","https://openalex.org/W6726584638"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W1924178503","https://openalex.org/W3135126032","https://openalex.org/W4308716060","https://openalex.org/W2358294942","https://openalex.org/W4385192698","https://openalex.org/W4367460280"],"abstract_inverted_index":{"Logic":[0],"diagnosis,":[1,121],"the":[2,43,107,112,117,135,164],"process":[3],"of":[4,45,62,137],"identifying":[5],"and":[6,25,77,122,129,157,175,177,187,192],"locating":[7],"possible":[8],"defects":[9],"in":[10,18,37,73,99],"failing":[11],"integrated":[12],"circuits,":[13],"is":[14,48,85,104,114,147],"a":[15,59,74,83,90,94,100,153,158],"key":[16],"step":[17],"yield":[19],"learning":[20],"for":[21,93,106,120,149],"both":[22],"technology":[23],"development":[24],"high-volume":[26,159],"manufacturing.":[27],"However,":[28],"resources":[29,69],"can":[30,166],"be":[31,54,71],"easily":[32],"wasted":[33],"if":[34,42,130],"diagnosis":[35,68,101,124],"results":[36,170,189],"no":[38],"meaningful":[39,105],"information,":[40],"or":[41,140],"type":[44],"diagnostic":[46,63],"result":[47,98,136],"not":[49],"actionable.":[50],"It":[51],"would":[52],"therefore":[53],"very":[55],"beneficial":[56],"to":[57,70,87,115],"have":[58],"comprehensive":[60],"preview":[61],"outcomes":[64],"beforehand,":[65],"which":[66],"allows":[67],"prioritized":[72],"more":[75],"reasonable":[76],"effective":[78],"way.":[79],"In":[80],"this":[81],"work,":[82],"methodology":[84,165],"developed":[86],"predict":[88,116],"whether":[89,123],"fail":[91],"log":[92],"given":[95],"design":[96],"will":[97],"outcome":[102],"that":[103,163],"purpose":[108],"at":[109],"hand.":[110],"Specifically,":[111],"aim":[113],"time":[118],"required":[119],"produces":[125],"any":[126],"defect":[127],"candidates,":[128],"so,":[131],"are":[132,185,200],"those":[133],"candidates":[134],"logic":[138],"failure":[139],"chain":[141],"failure.":[142],"Random":[143],"Forest":[144],"classification":[145],"algorithm":[146],"used":[148],"prediction.":[150],"Experiments":[151],"on":[152,180,195],"28nm":[154],"test":[155],"chip":[156],"90nm":[160],"part":[161],"illustrate":[162],"provide":[167],"accurate":[168],"prediction":[169],"(0.95+":[171,190],"precision,":[172],"0.9+":[173],"recall":[174,191],"F1-score,":[176],"0.96+":[178],"AUC":[179,194],"average)":[181,196],"when":[182,197],"two":[183,198],"classes":[184,199],"balanced,":[186],"satisfactory":[188],"0.98+":[193],"imbalanced.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}