{"id":"https://openalex.org/W4390606095","doi":"https://doi.org/10.1109/icm60448.2023.10378896","title":"An Analog Integrated, Low-Power, Area-Efficient, Gilbert, Modulo-based Classifier with Application to Lung-Cancer Classification","display_name":"An Analog Integrated, Low-Power, Area-Efficient, Gilbert, Modulo-based Classifier with Application to Lung-Cancer Classification","publication_year":2023,"publication_date":"2023-12-17","ids":{"openalex":"https://openalex.org/W4390606095","doi":"https://doi.org/10.1109/icm60448.2023.10378896"},"language":"en","primary_location":{"id":"doi:10.1109/icm60448.2023.10378896","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icm60448.2023.10378896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Microelectronics (ICM)","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/A5024524906","display_name":"Vassilis Alimisis","orcid":"https://orcid.org/0000-0002-2090-1493"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Vassilis Alimisis","raw_affiliation_strings":["National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","Department of Electrical and Computer Engineering, National Technical University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092886693","display_name":"Nikolaos P. Eleftheriou","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos P. Eleftheriou","raw_affiliation_strings":["National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","Department of Electrical and Computer Engineering, National Technical University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093657749","display_name":"Savvas Leventikidis","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Savvas Leventikidis","raw_affiliation_strings":["National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","Department of Electrical and Computer Engineering, National Technical University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013213336","display_name":"Paul P. Sotiriadis","orcid":"https://orcid.org/0000-0001-6030-4645"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Paul P. Sotiriadis","raw_affiliation_strings":["National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","Department of Electrical and Computer Engineering, National Technical University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"National Technical University of Athens,Department of Electrical and Computer Engineering,Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024524906"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1827601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"317","last_page":"320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9905999898910522,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7067817449569702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6709654331207275},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.5093947052955627},{"id":"https://openalex.org/keywords/cadence","display_name":"Cadence","score":0.5058996081352234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.503182590007782},{"id":"https://openalex.org/keywords/comparator","display_name":"Comparator","score":0.48860102891921997},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.4608997106552124},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4238555431365967},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.3859015703201294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3590627610683441},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3378887176513672},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.24427935481071472},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16144800186157227},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.1573857069015503},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.0799015462398529}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7067817449569702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6709654331207275},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.5093947052955627},{"id":"https://openalex.org/C2777125575","wikidata":"https://www.wikidata.org/wiki/Q14088448","display_name":"Cadence","level":2,"score":0.5058996081352234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.503182590007782},{"id":"https://openalex.org/C155745195","wikidata":"https://www.wikidata.org/wiki/Q1164179","display_name":"Comparator","level":3,"score":0.48860102891921997},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.4608997106552124},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4238555431365967},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.3859015703201294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3590627610683441},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3378887176513672},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.24427935481071472},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16144800186157227},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.1573857069015503},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0799015462398529},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icm60448.2023.10378896","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icm60448.2023.10378896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Microelectronics (ICM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.41999998688697815},{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2003522442","https://openalex.org/W2061860972","https://openalex.org/W2120461003","https://openalex.org/W2139016795","https://openalex.org/W2490662969","https://openalex.org/W2624989916","https://openalex.org/W2896122000","https://openalex.org/W2910166072","https://openalex.org/W2920878483","https://openalex.org/W3012277039","https://openalex.org/W3154409376","https://openalex.org/W3160875403","https://openalex.org/W4205409270","https://openalex.org/W4243832265","https://openalex.org/W4284705734","https://openalex.org/W4310034806","https://openalex.org/W4313886731","https://openalex.org/W4367320920","https://openalex.org/W4384067832"],"related_works":["https://openalex.org/W2374047926","https://openalex.org/W2394466068","https://openalex.org/W2381401419","https://openalex.org/W2383501440","https://openalex.org/W4312866165","https://openalex.org/W2957157835","https://openalex.org/W145653800","https://openalex.org/W83434975","https://openalex.org/W2393473353","https://openalex.org/W2606238806"],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"an":[3,61],"alternative":[4],"approach":[5],"to":[6],"develop":[7],"low-power":[8],"(744nW)":[9],"analog":[10,48,80],"classifiers":[11,81],"capable":[12],"of":[13,23,63,70],"efficiently":[14],"handling":[15],"multiple":[16],"input":[17],"features":[18],"while":[19],"maintaining":[20],"high":[21],"levels":[22],"accuracy":[24,62],"and":[25,35,44,107],"minimizing":[26],"power":[27],"consumption.":[28],"The":[29,47,88,96],"proposed":[30,97],"classifier":[31,49],"relies":[32],"on":[33],"Voting":[34],"Bayes":[36],"mathematical":[37],"models,":[38],"incorporating":[39],"Gilbert":[40],"two-signal":[41],"four-quadrant":[42],"multipliers":[43],"current":[45],"comparators.":[46],"is":[50,86,99],"validated":[51],"through":[52],"testing":[53],"with":[54,78],"a":[55,76,93],"real-world":[56],"lung-cancer":[57],"surgery":[58],"dataset,":[59],"achieving":[60],"75.45%.":[64],"It":[65],"predicts":[66],"all":[67],"testset":[68],"samples":[69],"patients":[71],"suffering":[72],"from":[73],"lung-cancer.":[74],"Additionally,":[75],"comparison":[77],"related":[79],"using":[82,101,109],"the":[83,102,110],"same":[84],"dataset":[85],"conducted.":[87],"models":[89],"are":[90],"trained":[91],"via":[92],"software-based":[94],"implementation.":[95],"architecture":[98],"realized":[100],"TSMC":[103],"90nm":[104],"CMOS":[105],"process":[106],"simulated":[108],"Cadence":[111],"IC":[112],"Suite.":[113]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
