{"id":"https://openalex.org/W4404032772","doi":"https://doi.org/10.1109/icccnt61001.2024.10724177","title":"Deep Learning and EHR-Driven Image Processing Framework for Lung Infection Detection in Healthcare Applications","display_name":"Deep Learning and EHR-Driven Image Processing Framework for Lung Infection Detection in Healthcare Applications","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404032772","doi":"https://doi.org/10.1109/icccnt61001.2024.10724177"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10724177","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt61001.2024.10724177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5114392042","display_name":"Saigurudatta Pamulaparthyvenkata","orcid":null},"institutions":[{"id":"https://openalex.org/I94734805","display_name":"Bryan College","ror":"https://ror.org/01bgnmj50","country_code":"US","type":"education","lineage":["https://openalex.org/I94734805"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saigurudatta Pamulaparthyvenkata","raw_affiliation_strings":["Independent researcher,Bryan,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Independent researcher,Bryan,Texas,USA","institution_ids":["https://openalex.org/I94734805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101168722","display_name":"Jitendra Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121988","display_name":"Film Independent","ror":"https://ror.org/036cy3843","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210121988"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jitendra Sharma","raw_affiliation_strings":["Independent Researcher,San Jose,California,USA"],"affiliations":[{"raw_affiliation_string":"Independent Researcher,San Jose,California,USA","institution_ids":["https://openalex.org/I4210121988"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105101303","display_name":"Rahul Dattangire","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118467","display_name":"Houston Independent School District","ror":"https://ror.org/01t5jw607","country_code":"US","type":"education","lineage":["https://openalex.org/I4210118467"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rahul Dattangire","raw_affiliation_strings":["Independent Researcher,Houston,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Independent Researcher,Houston,Texas,USA","institution_ids":["https://openalex.org/I4210118467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028143836","display_name":"Manish Vishwanath","orcid":null},"institutions":[{"id":"https://openalex.org/I4210117282","display_name":"Hanby Environmental (United States)","ror":"https://ror.org/02mdvw277","country_code":"US","type":"company","lineage":["https://openalex.org/I4210117282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manish Vishwanath","raw_affiliation_strings":["Independent Researcher,Katy,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Independent Researcher,Katy,Texas,USA","institution_ids":["https://openalex.org/I4210117282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114512184","display_name":"Sarika Mulukuntla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarika Mulukuntla","raw_affiliation_strings":["Health Information Technologists Specialist,Dallas,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Health Information Technologists Specialist,Dallas,Texas,USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025089752","display_name":"Preethi Preethi","orcid":"https://orcid.org/0000-0002-0032-481X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P. Preethi","raw_affiliation_strings":["Kongunadu College of Engineering and Technology,Department of CSE,Trichy"],"affiliations":[{"raw_affiliation_string":"Kongunadu College of Engineering and Technology,Department of CSE,Trichy","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028029577","display_name":"N Indhumathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N Indhumathi","raw_affiliation_strings":["Kongu Engineering College, Perundurai,Department of ECE,Erode,TamilNadu"],"affiliations":[{"raw_affiliation_string":"Kongu Engineering College, Perundurai,Department of ECE,Erode,TamilNadu","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5114392042"],"corresponding_institution_ids":["https://openalex.org/I94734805"],"apc_list":null,"apc_paid":null,"fwci":0.7839,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74857897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/computer-science","display_name":"Computer science","score":0.6521048545837402},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.6389102935791016},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5530171394348145},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5144074559211731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4624932110309601},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3733939528465271},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36553654074668884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521048545837402},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.6389102935791016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5530171394348145},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5144074559211731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4624932110309601},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3733939528465271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36553654074668884},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10724177","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt61001.2024.10724177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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":15,"referenced_works":["https://openalex.org/W2988014700","https://openalex.org/W4220822531","https://openalex.org/W4220863748","https://openalex.org/W4220896485","https://openalex.org/W4224274413","https://openalex.org/W4225154772","https://openalex.org/W4281971551","https://openalex.org/W4296962583","https://openalex.org/W4376870571","https://openalex.org/W4382135960","https://openalex.org/W4383888035","https://openalex.org/W4385652445","https://openalex.org/W4385974372","https://openalex.org/W4388333639","https://openalex.org/W4396546827"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W2802049774"],"abstract_inverted_index":{"Image":[0,92],"processing":[1,29,48,68,93,146],"plays":[2],"a":[3,149,255],"pivotal":[4],"role":[5],"in":[6,35,132,160,208,242],"healthcare":[7,74],"across":[8],"various":[9],"domains,":[10],"revolutionizing":[11],"diagnostics,":[12,57],"treatment,":[13,58],"and":[14,26,59,88,106,129,238],"patient":[15,60],"care.":[16,61],"In":[17,42],"medical":[18,40,81,99],"imaging,":[19],"such":[20],"as":[21],"X-rays,":[22],"CT":[23],"scans,":[24],"MRI,":[25],"ultrasound,":[27],"image":[28,32,47,67,145],"techniques":[30,69],"enhance":[31,95],"quality,":[33],"aiding":[34],"the":[36,44,64,96,140,154,161,165,186,192,196,199,204,209,212,221,226,233,236,243,250,264,273,283],"accurate":[37,86],"interpretation":[38],"of":[39,46,66,98,110,142,156,167,188,206,223,240,259,267,272],"conditions.":[41],"healthcare,":[43],"integration":[45],"with":[49,70,148,203],"data":[50,150],"analytics":[51,72,114,151],"holds":[52],"immense":[53],"potential":[54],"to":[55,84,120,124,190],"revolutionize":[56],"By":[62],"combining":[63],"power":[65],"advanced":[71],"algorithms,":[73],"providers":[75],"can":[76,94],"extract":[77],"valuable":[78],"insights":[79],"from":[80],"images,":[82,100],"leading":[83],"more":[85,104],"diagnoses":[87],"personalized":[89],"treatment":[90],"plans.":[91],"quality":[97],"making":[101,133],"subtle":[102],"abnormalities":[103],"visible":[105],"enabling":[107],"automated":[108],"analysis":[109,247],"large":[111],"datasets.":[112],"Data":[113],"techniques,":[115],"deep":[116,216,229,285],"learning":[117,217,230,286],"is":[118,201,218],"applied":[119],"these":[121],"processed":[122],"images":[123,189],"identify":[125],"patterns,":[126],"predict":[127],"outcomes,":[128],"assist":[130],"clinicians":[131],"informed":[134],"decisions.":[135],"This":[136],"paper":[137,171],"focused":[138],"on":[139],"development":[141],"an":[143],"effective":[144],"technique":[147],"model":[152,231,253,275],"for":[153,185,220,235,263],"detection":[155,257],"infection":[157],"or":[158],"diseases":[159,169,241],"lung.":[162],"To":[163],"evaluate":[164],"characteristics":[166],"lung":[168,244,268],"this":[170],"proposed":[172,180,251,274],"point":[173,183],"estimation":[174,184,222,237],"centroid":[175],"Deep":[176],"Learning":[177],"(PEC-DL).":[178],"The":[179,270],"PEC-DL":[181,252],"uses":[182],"segmentation":[187,200],"perform":[191],"feature":[193],"extraction.":[194],"With":[195],"estimated":[197,215,227],"points":[198],"performed":[202],"extraction":[205],"features":[207,213,228],"images.":[210],"Once":[211],"are":[214],"implemented":[219],"features.":[224],"Through":[225],"performs":[232],"classification":[234,266],"prediction":[239],"region.":[245],"Simulation":[246],"demonstrated":[248],"that":[249],"achieves":[254],"higher":[256],"rate":[258],"$\\mathbf{9":[260],"8":[261],"\\%}$":[262],"correct":[265],"diseases.":[269],"performance":[271,281],"exhibits":[276],"$\\sim":[277],"12":[278],"\\%$":[279],"improved":[280],"than":[282],"conventional":[284],"model.":[287]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
