{"id":"https://openalex.org/W2966346359","doi":"https://doi.org/10.1145/3340997.3341000","title":"Diagnosis of Methylmalonic Acidemia using Machine Learning Methods","display_name":"Diagnosis of Methylmalonic Acidemia using Machine Learning Methods","publication_year":2019,"publication_date":"2019-06-21","ids":{"openalex":"https://openalex.org/W2966346359","doi":"https://doi.org/10.1145/3340997.3341000","mag":"2966346359"},"language":"en","primary_location":{"id":"doi:10.1145/3340997.3341000","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340997.3341000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 4th International Conference on Machine Learning Technologies","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/A5100353748","display_name":"Xin Li","orcid":"https://orcid.org/0000-0001-8328-4894"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Li","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075894937","display_name":"Xiaoxing Yang","orcid":"https://orcid.org/0000-0001-8569-2832"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxing Yang","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101707990","display_name":"Wushao Wen","orcid":"https://orcid.org/0000-0003-4819-4679"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wushao Wen","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100353748"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09694578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11027","display_name":"Metabolism and Genetic Disorders","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1308","display_name":"Clinical Biochemistry"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11027","display_name":"Metabolism and Genetic Disorders","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1308","display_name":"Clinical Biochemistry"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9700999855995178,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/methylmalonic-acidemia","display_name":"Methylmalonic acidemia","score":0.8404419422149658},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7626975774765015},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6883922815322876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6114723682403564},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5547124147415161},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32760506868362427},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21207216382026672},{"id":"https://openalex.org/keywords/pediatrics","display_name":"Pediatrics","score":0.177604079246521}],"concepts":[{"id":"https://openalex.org/C2778159418","wikidata":"https://www.wikidata.org/wiki/Q742500","display_name":"Methylmalonic acidemia","level":2,"score":0.8404419422149658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7626975774765015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6883922815322876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6114723682403564},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5547124147415161},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32760506868362427},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21207216382026672},{"id":"https://openalex.org/C187212893","wikidata":"https://www.wikidata.org/wiki/Q123028","display_name":"Pediatrics","level":1,"score":0.177604079246521}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340997.3341000","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340997.3341000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 4th International Conference on Machine Learning Technologies","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":26,"referenced_works":["https://openalex.org/W1554944419","https://openalex.org/W1896989020","https://openalex.org/W1901616594","https://openalex.org/W1929592705","https://openalex.org/W1986328771","https://openalex.org/W1988195734","https://openalex.org/W2008328868","https://openalex.org/W2019338079","https://openalex.org/W2050006661","https://openalex.org/W2084791688","https://openalex.org/W2102017903","https://openalex.org/W2109943925","https://openalex.org/W2123741762","https://openalex.org/W2158698691","https://openalex.org/W2468477102","https://openalex.org/W2487770199","https://openalex.org/W2555082815","https://openalex.org/W2581082771","https://openalex.org/W2610096391","https://openalex.org/W2741016737","https://openalex.org/W2787894218","https://openalex.org/W2807654820","https://openalex.org/W2952215077","https://openalex.org/W2963156201","https://openalex.org/W3001645704","https://openalex.org/W6611069813"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Methylmalonic":[0],"acidemia":[1],"(MMA)":[2],"is":[3,141,171],"an":[4,180],"autosomal":[5],"recessive":[6],"metabolic":[7],"disorder.":[8],"Traditional":[9],"diagnosis":[10,49,129,144,162,182],"needs":[11],"physicians'":[12,54],"personal":[13,55],"level":[14,56],"of":[15,57,109,163],"professional":[16,58,184],"medical":[17,59,185],"knowledge":[18,60],"and":[19,39,50,61,95,107,127,138],"clinical":[20,62],"experience.":[21,63],"In":[22],"this":[23],"paper,":[24],"we":[25,73],"employ":[26],"machine":[27,67,79,157,175],"learning":[28,68,80,158,176],"methods":[29,81],"to":[30,45,160,173,178],"diagnose":[31],"MMA":[32,87,164],"based":[33,130,145],"on":[34,53,131,146],"patients'":[35],"laboratory":[36,40],"blood":[37,139],"tests":[38,137,140],"urine":[41,136],"tests,":[42],"in":[43,150],"order":[44],"make":[46],"a":[47],"timely":[48],"reduce":[51],"dependence":[52],"By":[64],"comparing":[65],"different":[66],"algorithms":[69,159],"for":[70,85],"diagnosing":[71,86],"MMA,":[72],"obtain":[74,92],"the":[75,124,132,161],"following":[76],"conclusions:":[77],"(a)":[78],"can":[82,165],"perform":[83],"well":[84],"(all":[88],"established":[89],"predictive":[90],"models":[91,177],"high":[93],"accuracies":[94],"AUC":[96],"values":[97],"which":[98],"are":[99,112],"greater":[100],"than":[101,115,143],"0.85":[102],"over":[103],"all":[104],"data":[105,133],"sets,":[106],"some":[108],"these":[110],"results":[111],"even":[113],"more":[114],"0.98);":[116],"(b)":[117],"random":[118],"forest":[119],"algorithm":[120],"performs":[121],"best":[122],"among":[123],"compared":[125],"algorithms;":[126],"(c)":[128],"combining":[134],"both":[135],"better":[142],"single":[147],"test":[148],"alone":[149],"general.":[151],"The":[152],"conclusions":[153],"show":[154],"that":[155],"applying":[156],"achieve":[166],"good":[167],"performance.":[168],"Thus,":[169],"it":[170],"credible":[172],"build":[174],"give":[179],"initial":[181],"without":[183],"knowledge.":[186]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
