{"id":"https://openalex.org/W7225636771","doi":"https://doi.org/10.68314/4akfkj55","title":"AI-Powered Behavioral Health Monitoring in Telemedicine Platforms: A 72-Hour Early Warning Framework Using Passive Digital Biomarkers and LSTM Networks","display_name":"AI-Powered Behavioral Health Monitoring in Telemedicine Platforms: A 72-Hour Early Warning Framework Using Passive Digital Biomarkers and LSTM Networks","publication_year":2026,"publication_date":"2026-11-08","ids":{"openalex":"https://openalex.org/W7225636771","doi":"https://doi.org/10.68314/4akfkj55"},"language":"en","primary_location":{"id":"doi:10.68314/4akfkj55","doi":"https://doi.org/10.68314/4akfkj55","is_oa":true,"landing_page_url":"https://doi.org/10.68314/4akfkj55","pdf_url":"https://ojs.orbisjmhs.org/index.php/ojmhs/article/download/15/16","source":{"id":"https://openalex.org/S7407065153","display_name":"Orbis Journal of Medical and Health Sciences","issn_l":"3143-8725","issn":["3143-8725"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Orbis Journal of Medical and Health Sciences","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ojs.orbisjmhs.org/index.php/ojmhs/article/download/15/16","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120266036","display_name":"Sumanth Banakar","orcid":"https://orcid.org/0009-0004-3316-8106","observed_orcids":["https://orcid.org/0009-0004-3316-8106"]},"institutions":[{"id":"https://openalex.org/I276309446","display_name":"University of the Cumberlands","ror":"https://ror.org/05jz3sn81","country_code":"US","type":"education","lineage":["https://openalex.org/I276309446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sumanth Banakar","raw_affiliation_strings":["University of the Cumberlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of the Cumberlands","institution_ids":["https://openalex.org/I276309446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120266037","display_name":"Venkatesh Ankarla Sri Ramuloo","orcid":"https://orcid.org/0009-0007-0837-5914","observed_orcids":["https://orcid.org/0009-0007-0837-5914"]},"institutions":[{"id":"https://openalex.org/I276309446","display_name":"University of the Cumberlands","ror":"https://ror.org/05jz3sn81","country_code":"US","type":"education","lineage":["https://openalex.org/I276309446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Venkatesh Ankarla Sri Ramuloo","raw_affiliation_strings":["University of the Cumberlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of the Cumberlands","institution_ids":["https://openalex.org/I276309446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161341210","display_name":"Kasi Viswanath Bolla","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I276309446","display_name":"University of the Cumberlands","ror":"https://ror.org/05jz3sn81","country_code":"US","type":"education","lineage":["https://openalex.org/I276309446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kasi Viswanath Bolla","raw_affiliation_strings":["University of the Cumberlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of the Cumberlands","institution_ids":["https://openalex.org/I276309446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103995405","display_name":"Greg Benson","orcid":"https://orcid.org/0009-0005-0535-5593","observed_orcids":["https://orcid.org/0009-0005-0535-5593"]},"institutions":[{"id":"https://openalex.org/I130555825","display_name":"Faulkner University","ror":"https://ror.org/048kc5t54","country_code":"US","type":"education","lineage":["https://openalex.org/I130555825"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Greg M. Benson","raw_affiliation_strings":["Faulkner University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faulkner University","institution_ids":["https://openalex.org/I130555825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134427997","display_name":"Lourdu Akhila Yeruva","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lourdu Akhila Yeruva","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126930364","display_name":"Rohit Reddy Gaddam","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohit Reddy Gaddam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.33739998936653137,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.33739998936653137,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.25999999046325684,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.04919999837875366,"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/telemedicine","display_name":"telemedicine","score":0.7649999856948853},{"id":"https://openalex.org/keywords/early-warning-systems","display_name":"early warning systems","score":0.6800000071525574},{"id":"https://openalex.org/keywords/long-short-term-memory-networks","display_name":"long short-term memory networks","score":0.7730000019073486},{"id":"https://openalex.org/keywords/multimodal-sensing","display_name":"multimodal sensing","score":0.675000011920929},{"id":"https://openalex.org/keywords/remote-patient-monitoring","display_name":"remote patient monitoring","score":0.7279999852180481},{"id":"https://openalex.org/keywords/sleep-architecture","display_name":"sleep architecture","score":0.6209999918937683},{"id":"https://openalex.org/keywords/physical-activity-patterns","display_name":"physical activity patterns","score":0.8009999990463257},{"id":"https://openalex.org/keywords/physiological-signals","display_name":"physiological signals","score":0.9100000262260437},{"id":"https://openalex.org/keywords/depression-detection","display_name":"depression detection","score":0.3720000088214874},{"id":"https://openalex.org/keywords/warning-lead-time","display_name":"warning lead time","score":0.5199999809265137},{"id":"https://openalex.org/keywords/model-calibration","display_name":"model calibration","score":0.40299999713897705}],"concepts":[{"id":"https://openalex.org/C2779891985","wikidata":"https://www.wikidata.org/wiki/Q46994","display_name":"Telemedicine","level":3,"score":0.7269999980926514},{"id":"https://openalex.org/C2777671062","wikidata":"https://www.wikidata.org/wiki/Q6889402","display_name":"Early warning score","level":2,"score":0.6678000092506409},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.6168000102043152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.612500011920929},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5393000245094299},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.5253999829292297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5217000246047974},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C2780433410","wikidata":"https://www.wikidata.org/wiki/Q5276090","display_name":"Digital health","level":3,"score":0.46639999747276306},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4560000002384186},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44119998812675476},{"id":"https://openalex.org/C35405484","wikidata":"https://www.wikidata.org/wiki/Q4967066","display_name":"Brier score","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C175079658","wikidata":"https://www.wikidata.org/wiki/Q7312165","display_name":"Remote patient monitoring","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33869999647140503},{"id":"https://openalex.org/C2779296788","wikidata":"https://www.wikidata.org/wiki/Q5326904","display_name":"Early warning system","level":3,"score":0.3361000120639801},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3190999925136566},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.3109999895095825},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C83804111","wikidata":"https://www.wikidata.org/wiki/Q1063558","display_name":"Behavioral pattern","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C2778996325","wikidata":"https://www.wikidata.org/wiki/Q422201","display_name":"Actigraphy","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C2779363104","wikidata":"https://www.wikidata.org/wiki/Q17069079","display_name":"mHealth","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C2777428918","wikidata":"https://www.wikidata.org/wiki/Q5690807","display_name":"Health assessment","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.68314/4akfkj55","doi":"https://doi.org/10.68314/4akfkj55","is_oa":true,"landing_page_url":"https://doi.org/10.68314/4akfkj55","pdf_url":"https://ojs.orbisjmhs.org/index.php/ojmhs/article/download/15/16","source":{"id":"https://openalex.org/S7407065153","display_name":"Orbis Journal of Medical and Health Sciences","issn_l":"3143-8725","issn":["3143-8725"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Orbis Journal of Medical and Health Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.68314/4akfkj55","doi":"https://doi.org/10.68314/4akfkj55","is_oa":true,"landing_page_url":"https://doi.org/10.68314/4akfkj55","pdf_url":"https://ojs.orbisjmhs.org/index.php/ojmhs/article/download/15/16","source":{"id":"https://openalex.org/S7407065153","display_name":"Orbis Journal of Medical and Health Sciences","issn_l":"3143-8725","issn":["3143-8725"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Orbis Journal of Medical and Health Sciences","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.98580002784729,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225636771.pdf","grobid_xml":"https://content.openalex.org/works/W7225636771.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1894490285","https://openalex.org/W2132322340","https://openalex.org/W2392412101","https://openalex.org/W2520441859","https://openalex.org/W2541884796","https://openalex.org/W2759174152","https://openalex.org/W2894899985","https://openalex.org/W2912581524","https://openalex.org/W2915095068","https://openalex.org/W2964010366","https://openalex.org/W2964696298","https://openalex.org/W2996331899","https://openalex.org/W2999309192","https://openalex.org/W3004612364","https://openalex.org/W3013038708","https://openalex.org/W3046183292","https://openalex.org/W3165173117","https://openalex.org/W4386038850","https://openalex.org/W4386568923","https://openalex.org/W4412432520","https://openalex.org/W4413116978","https://openalex.org/W4414093102"],"related_works":["https://openalex.org/W7171744471","https://openalex.org/W7155361569","https://openalex.org/W6949907817","https://openalex.org/W4415368824","https://openalex.org/W7220232633","https://openalex.org/W2408553341","https://openalex.org/W7162670771","https://openalex.org/W4417404766","https://openalex.org/W7213322769","https://openalex.org/W7154480535"],"abstract_inverted_index":{"Requiring":[0],"patients":[1,66],"to":[2,40,46,139,153,194],"complete":[3],"screening":[4],"questionnaires":[5],"periodically":[6],"is":[7],"a":[8,99,135,175,184,190,222,230],"challenge":[9],"for":[10,129,209,235],"early":[11],"detection":[12],"of":[13,54,110,180],"deterioration":[14],"in":[15,18],"behavioral":[16,48,214],"health":[17,49,215],"telemedicine.":[19],"This":[20],"study":[21],"suggests":[22],"an":[23,107],"Artificial":[24],"Intelligence":[25],"system":[26],"that":[27],"uses":[28],"Passive":[29],"Digital":[30],"Biomarkers,":[31],"derived":[32],"from":[33,36,60,72],"multimodal":[34],"sensing":[35],"remote":[37],"monitoring":[38],"devices,":[39],"be":[41],"integrated":[42],"at":[43,189],"the":[44,61,121,154],"feature-level":[45],"predict":[47],"events":[50],"72":[51],"hours":[52],"ahead":[53],"time.":[55],"The":[56,113,142,172,226],"data":[57],"used":[58],"were":[59],"TIHM":[62],"dataset":[63],"with":[64,98,106,118,183,202,221],"56":[65],"and":[67,83,131,212,232],"5,096":[68],"patient":[69],"day":[70,182],"records,":[71],"which":[73],"we":[74],"engineered":[75],"15":[76],"features":[77],"encompassing":[78],"activity":[79],"patterns,":[80],"sleep":[81],"architecture,":[82],"physiological":[84],"signals.":[85],"We":[86],"benchmarked":[87],"baseline":[88,156],"machine":[89],"learning":[90],"models":[91],"(Logistic":[92],"Regression,":[93],"Random":[94],"Forest,":[95],"Gradient":[96],"Boosting)":[97],"temporal":[100,203],"Long":[101],"Short-Term":[102],"Memory":[103],"(LSTM)":[104],"network":[105],"input":[108],"window":[109],"7":[111],"days.":[112],"model":[114,144,173],"performance":[115],"was":[116],"assessed":[117],"area":[119],"under":[120],"receiver":[122],"operating":[123],"characteristic":[124],"curve":[125],"(AUC-ROC),":[126],"Brier":[127],"score":[128],"calibration,":[130],"statistical":[132],"comparison":[133],"through":[134],"null-centered":[136],"bootstrap":[137],"approximation":[138],"DeLong's":[140],"test.":[141],"LSTM":[143],"achieved":[145],"significantly":[146],"higher":[147],"discrimination":[148],"(AUC":[149],"=":[150,160,163],"0.808)":[151],"compared":[152],"best":[155],"(Random":[157],"Forest:":[158],"AUC":[159],"0.711;":[161],"\u0394AUC":[162],"\u22120.097,":[164],"95%":[165],"CI":[166],"[\u22120.142,":[167],"\u22120.052],":[168],"p":[169],"<":[170],"0.001).":[171],"gave":[174],"median":[176],"warning":[177],"lead":[178],"time":[179],"1.0":[181],"tolerable":[185],"false":[186],"positive":[187],"rate":[188],"clinically":[191],"calibrated":[192],"threshold":[193],"achieve":[195],"90%":[196],"sensitivity.":[197],"Multimodal":[198],"passive":[199],"sensing,":[200],"coupled":[201],"deep":[204],"learning,":[205],"holds":[206],"great":[207],"promise":[208],"more":[210],"precise":[211],"earlier":[213],"monitoring,":[216],"but":[217],"requires":[218],"external":[219],"validation":[220],"larger":[223],"sample":[224],"size.":[225],"proposed":[227],"framework":[228],"sets":[229],"repeatable":[231],"privacy-friendly":[233],"groundwork":[234],"proactive":[236],"telemedicine":[237],"interventions.":[238]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}