{"id":"https://openalex.org/W7160631983","doi":"https://doi.org/10.48550/arxiv.2605.05963","title":"TheraAgent: Self-Improving Therapeutic Agent for Precise and Comprehensive Treatment Planning","display_name":"TheraAgent: Self-Improving Therapeutic Agent for Precise and Comprehensive Treatment Planning","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160631983","doi":"https://doi.org/10.48550/arxiv.2605.05963"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05963","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05963","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.05963","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135653876","display_name":"Junkai Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Junkai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135675291","display_name":"Yunghwei Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Yunghwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126377344","display_name":"Tianyi Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Tianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135641520","display_name":"Zheng Long Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Zheng Long","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135657044","display_name":"Weizhi Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Weizhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135721984","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-5058-7781"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5145999789237976,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5145999789237976,"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"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.18649999797344208,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.11400000005960464,"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/task","display_name":"Task (project management)","score":0.6348000168800354},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5963000059127808},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5515999794006348},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.5199000239372253},{"id":"https://openalex.org/keywords/mirroring","display_name":"Mirroring","score":0.4961000084877014},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47290000319480896},{"id":"https://openalex.org/keywords/harm","display_name":"Harm","score":0.4490000009536743},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.41280001401901245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6492999792098999},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6348000168800354},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5963000059127808},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.5227000117301941},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.5199000239372253},{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47290000319480896},{"id":"https://openalex.org/C2777363581","wikidata":"https://www.wikidata.org/wiki/Q15098235","display_name":"Harm","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36800000071525574},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3418999910354614},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3093999922275543},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2712000012397766},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.2639999985694885}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05963","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05963","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.05963","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05963","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Formulating":[0],"a":[1,6,14,100],"treatment":[2,41,74],"plan":[3],"is":[4],"inherently":[5],"complex":[7],"reasoning":[8,66],"and":[9,38,81,87,124,140,149],"refinement":[10],"task":[11],"rather":[12],"than":[13],"simple":[15],"generation":[16,56],"problem.":[17],"However,":[18],"existing":[19],"large":[20],"language":[21],"models":[22],"(LLMs)":[23],"mainly":[24],"rely":[25],"on":[26,119],"one-shot":[27,55],"output":[28],"without":[29],"explicit":[30],"verification,":[31],"which":[32],"may":[33],"result":[34],"in":[35,122],"rough,":[36],"incomplete,":[37],"potentially":[39],"unsafe":[40],"plans.":[42],"To":[43,91],"address":[44],"these":[45],"limitations,":[46],"we":[47,97],"propose":[48],"TheraAgent,":[49],"an":[50,58,131],"agentic":[51],"framework":[52,77],"that":[53],"replaces":[54],"with":[57,137],"iterative":[59],"generate-judge-refine":[60],"pipeline.":[61],"By":[62],"mirroring":[63],"the":[64,93,106,144,153],"actual":[65],"process":[67],"of":[68,155],"human":[69],"experts":[70],"who":[71],"iteratively":[72],"revise":[73],"plans,":[75],"our":[76,156],"progressively":[78],"transforms":[79],"coarse":[80],"incomplete":[82],"drafts":[83],"into":[84,105],"precise,":[85],"comprehensive,":[86],"safer":[88],"therapeutic":[89],"regimens.":[90],"facilitate":[92],"critical":[94],"judge":[95],"component,":[96],"introduce":[98],"TheraJudge,":[99],"treatment-specific":[101],"evaluation":[102],"module":[103],"integrated":[104],"inference":[107],"loop":[108],"to":[109],"enforce":[110],"clinical":[111],"standards.":[112],"Experiments":[113],"show":[114],"TheraAgent":[115],"achieves":[116],"state-of-the-art":[117],"results":[118],"HealthBench,":[120],"leading":[121],"Accuracy":[123],"Completeness.":[125],"In":[126],"expert":[127],"evaluations,":[128],"it":[129],"attains":[130],"86%":[132],"win":[133],"rate":[134],"against":[135],"physicians,":[136],"superior":[138],"Targeting":[139],"Harm":[141],"Control.":[142],"Moreover,":[143],"highly":[145],"agreement":[146],"between":[147],"TheraJudge":[148],"HealthBench":[150],"evaluations":[151],"confirms":[152],"reliability":[154],"framework.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-09T00:00:00"}
