{"id":"https://openalex.org/W3039294188","doi":"https://doi.org/10.1145/3406601.3406613","title":"A System to Estimate the Amount and Calories of Food that Elderly People in the Hospital Consume","display_name":"A System to Estimate the Amount and Calories of Food that Elderly People in the Hospital Consume","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3039294188","doi":"https://doi.org/10.1145/3406601.3406613","mag":"3039294188"},"language":"en","primary_location":{"id":"doi:10.1145/3406601.3406613","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3406601.3406613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Conference on Advances in Information Technology","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/A5040551911","display_name":"Pisol Ruenin","orcid":null},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Pisol Ruenin","raw_affiliation_strings":["Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089160662","display_name":"Jakramate Bootkrajang","orcid":"https://orcid.org/0000-0002-9158-1570"},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Jakramate Bootkrajang","raw_affiliation_strings":["Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026076097","display_name":"Jakarin Chawachat","orcid":null},"institutions":[{"id":"https://openalex.org/I48076826","display_name":"Chiang Mai University","ror":"https://ror.org/05m2fqn25","country_code":"TH","type":"education","lineage":["https://openalex.org/I48076826"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Jakarin Chawachat","raw_affiliation_strings":["Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand"],"affiliations":[{"raw_affiliation_string":"Data Science Research Center, Department of Computer Science, Chiang Mai University, Chiang Mai, Thailand","institution_ids":["https://openalex.org/I48076826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040551911"],"corresponding_institution_ids":["https://openalex.org/I48076826"],"apc_list":null,"apc_paid":null,"fwci":0.8879,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76804374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"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/T10866","display_name":"Nutritional Studies and Diet","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"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/calorie","display_name":"Calorie","score":0.9117220640182495},{"id":"https://openalex.org/keywords/food-energy","display_name":"Food energy","score":0.7526829838752747},{"id":"https://openalex.org/keywords/malnutrition","display_name":"Malnutrition","score":0.6853554248809814},{"id":"https://openalex.org/keywords/food-consumption","display_name":"Food consumption","score":0.6020599603652954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47542908787727356},{"id":"https://openalex.org/keywords/food-intake","display_name":"Food intake","score":0.4197680354118347},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.3586142659187317},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3510548770427704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33886080980300903},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.30291318893432617},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2047717571258545},{"id":"https://openalex.org/keywords/agricultural-economics","display_name":"Agricultural economics","score":0.12184655666351318}],"concepts":[{"id":"https://openalex.org/C40438245","wikidata":"https://www.wikidata.org/wiki/Q130964","display_name":"Calorie","level":2,"score":0.9117220640182495},{"id":"https://openalex.org/C116019233","wikidata":"https://www.wikidata.org/wiki/Q186205","display_name":"Food energy","level":2,"score":0.7526829838752747},{"id":"https://openalex.org/C551997983","wikidata":"https://www.wikidata.org/wiki/Q12167","display_name":"Malnutrition","level":2,"score":0.6853554248809814},{"id":"https://openalex.org/C2987526018","wikidata":"https://www.wikidata.org/wiki/Q213449","display_name":"Food consumption","level":2,"score":0.6020599603652954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47542908787727356},{"id":"https://openalex.org/C3018685816","wikidata":"https://www.wikidata.org/wiki/Q213449","display_name":"Food intake","level":2,"score":0.4197680354118347},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.3586142659187317},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3510548770427704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33886080980300903},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.30291318893432617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2047717571258545},{"id":"https://openalex.org/C48824518","wikidata":"https://www.wikidata.org/wiki/Q396340","display_name":"Agricultural economics","level":1,"score":0.12184655666351318},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3406601.3406613","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3406601.3406613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Conference on Advances in Information Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1033503530","https://openalex.org/W1982918230","https://openalex.org/W2028888808","https://openalex.org/W2107722796","https://openalex.org/W2563053307","https://openalex.org/W2903855512","https://openalex.org/W2954779813","https://openalex.org/W3200473828","https://openalex.org/W4245313553","https://openalex.org/W4245854086"],"related_works":["https://openalex.org/W3039294188","https://openalex.org/W3030114418","https://openalex.org/W4376508560","https://openalex.org/W2811122680","https://openalex.org/W2135598475","https://openalex.org/W2021542160","https://openalex.org/W3081603768","https://openalex.org/W1981042807","https://openalex.org/W4244375248","https://openalex.org/W2942313158"],"abstract_inverted_index":{"Malnutrition":[0],"in":[1,12,47,87,94],"the":[2,10,22,28,45,50,55,58,77,82,85,88,121,126,171,176,187,190,213,219,223,230],"elderly":[3,11,23,29,86,220],"is":[4,200],"an":[5],"important":[6],"issue,":[7],"especially":[8],"for":[9],"hospitals.":[13],"In":[14,68,120,170],"general,":[15],"nutritionists":[16,53],"calculate":[17],"energy":[18,61],"from":[19,155],"foods":[20],"that":[21,84,166,195],"need":[24],"each":[25],"day.":[26],"If":[27],"eat":[30],"less":[31],"food":[32,40,63,83,97,109,113,153,163,192,225],"and":[33,54,60,79,100,111,116,130],"do":[34],"not":[35],"receive":[36],"enough":[37],"energy,":[38],"supplementary":[39],"must":[41],"be":[42],"provided.":[43],"Currently,":[44],"problems":[46],"hospitals":[48],"are":[49],"lack":[51],"of":[52,57,62,81,150,215],"calculation":[56],"amount":[59,78],"takes":[64],"a":[65,73,95,134,143,181,202,208],"long":[66],"time.":[67],"this":[69],"research,":[70],"we":[71,124,174,206],"present":[72],"system":[74,104],"to":[75,211],"estimate":[76],"calories":[80,117,216,228],"hospital":[89,231],"consume":[90],"by":[91,218,221],"taking":[92],"pictures":[93],"divided":[96],"tray":[98],"before":[99],"after":[101],"consumption.":[102],"Our":[103,137],"has":[105],"three":[106],"main":[107],"parts:":[108],"detection":[110],"classification,":[112],"weight":[114,226],"estimation,":[115],"estimation":[118],"application.":[119],"first":[122],"part,":[123,173],"use":[125,175],"Faster":[127],"R-CNN":[128],"technique":[129],"select":[131],"ResNet-50":[132],"as":[133,184],"pre-trained":[135,182],"model.":[136],"prediction":[138],"model":[139,183],"was":[140],"trained":[141],"on":[142],"Suandok":[144],"Hospital":[145],"Food":[146],"Images":[147],"Dataset":[148],"(SH-FID)":[149],"16,":[151],"067":[152],"images":[154,164,193],"39":[156],"different":[157],"classes.":[158],"The":[159],"result":[160],"with":[161,189],"4017":[162,191],"showed":[165],"mAP":[167],"=":[168,197],"73.354.":[169],"second":[172],"CNN":[177],"technique,":[178],"which":[179,199],"uses":[180],"InceptionResNetV2.":[185],"From":[186],"experiment":[188],"found":[194],"MAPE":[196],"16.9729,":[198],"considered":[201],"good":[203],"prediction.":[204],"Finally,":[205],"created":[207],"web":[209],"application":[210],"display":[212],"number":[214],"consumed":[217],"converting":[222],"calculated":[224],"into":[227],"using":[229],"reference":[232],"table.":[233]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}