Research on the Development and Validation of Personalized Exercise Prescription System for Breast Cancer Patients Based on Large Language Models
11. august 2026 oppdatert av: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
The goal of this observational study is to develop and evaluate a large language model (LLM)-based decision support system for exercise prescription in breast cancer patients, aiming to provide personalized decision-making support for postoperative breast cancer rehabilitation.
The main questions it aims to answer are:
How accurate, personalized, and safe are the exercise prescriptions generated by the fine-tuned LLM? How does the model's performance compare with other mainstream or non-fine-tuned models across different stages and subtypes of breast cancer? Participants are postoperative breast cancer rehabilitation patients treated at Sun Yat-sen Memorial Hospital of Sun Yat-sen University. They will have demographic, tumor, treatment, and physical fitness data collected; receive personalized exercise prescriptions automatically generated by the LLM-based system; and provide subjective evaluations on the feasibility and executability of the prescriptions.
Studieoversikt
Status
Har ikke rekruttert ennå
Forhold
Studietype
Observasjonsmessig
Registrering (Antatt)
40
Kontakter og plasseringer
Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.
Studiesteder
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Guangdong
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Guangzhou, Guangdong, Kina, 510000
- Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
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Ta kontakt med:
- jianli Zhao
- Telefonnummer: 15920589334
- E-post: zhaojianli1988@126.com
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Ta kontakt med:
- E-post: zhaojianli1988@126.com
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Deltakelseskriterier
Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Voksen
- Eldre voksen
Tar imot friske frivillige
Nei
Prøvetakingsmetode
Ikke-sannsynlighetsprøve
Studiepopulasjon
Patients with breast cancer who have completed primary surgery and entered the postoperative rehabilitation stage at Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Guangzhou, China).All participants receive individualized exercise prescriptions generated by large language models under physician supervision and approval, and their feedback on the feasibility of these prescriptions is collected.
Beskrivelse
Inclusion Criteria:
- Adult patients aged 18-75 years with early-stage breast cancer who have undergone surgical treatment, such as mastectomy or breast-conserving surgery.
- The patients had clear clinical diagnosis and complete electronic medical record information (including demographic information, tumor stage and classification, treatment history, physical performance evaluation data, etc.).
Exclusion Criteria:
- Presence of severe postoperative complications or comorbidities (e.g., uncontrolled cardiac or pulmonary disease) that may interfere with participation in rehabilitation or pose a safety risk.
Studieplan
Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.
Hvordan er studiet utformet?
Designdetaljer
Kohorter og intervensjoner
Gruppe / Kohort |
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Postoperative breast cancer patients receiving LLM-based exercise prescription evaluation
Postoperative breast cancer patients at Sun Yat-sen Memorial Hospital will have clinical and physical data collected.
Each patient receives an exercise prescription generated by a fine-tuned large language model (LLM)-based decision support system and provides feedback on its feasibility.
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Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Overall Quality Score of Exercise Prescriptions Based on a Five-Dimensional Expert Evaluation Framework
Tidsramme: From enrollment to completion of prescription evaluation at 1 week
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Each exercise prescription will be independently evaluated by six multidisciplinary experts across five dimensions: scientific rationale, personalization, comprehensiveness, safety, and feasibility.
Each dimension will be rated on a 5-point Likert scale from 1 to 5. The five dimension scores will be summed to generate an overall quality score ranging from 5 to 25, with higher scores indicating better overall prescription quality.
For each prescription, the mean overall score across the six experts will be used for analysis.
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From enrollment to completion of prescription evaluation at 1 week
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Sekundære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Subgroup-Specific Scientific Rationale and Safety Scores of Model-Generated Exercise Prescriptions
Tidsramme: From enrollment to completion of prescription evaluation at 1 week
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Model performance will be evaluated across predefined subgroups based on age, breast cancer stage, molecular subtype, surgical procedure, and treatment modality.
Scientific rationale and safety will each be rated on a 1-5 Likert scale, with higher scores indicating better performance.
Differences across models and subgroups will be assessed using two-way ANOVA or generalized linear models, including interaction terms between model type and patient characteristics.
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From enrollment to completion of prescription evaluation at 1 week
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Samarbeidspartnere og etterforskere
Det er her du vil finne personer og organisasjoner som er involvert i denne studien.
Studierekorddatoer
Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.
Studer hoveddatoer
Studiestart (Antatt)
15. september 2026
Primær fullføring (Antatt)
1. juli 2027
Studiet fullført (Antatt)
31. desember 2027
Datoer for studieregistrering
Først innsendt
11. august 2026
Først innsendt som oppfylte QC-kriteriene
11. august 2026
Først lagt ut (Faktiske)
17. august 2026
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
17. august 2026
Siste oppdatering sendt inn som oppfylte QC-kriteriene
11. august 2026
Sist bekreftet
1. august 2026
Mer informasjon
Begreper knyttet til denne studien
Ytterligere relevante MeSH-vilkår
Andre studie-ID-numre
- SYSKY-2025-786-02
Legemiddel- og utstyrsinformasjon, studiedokumenter
Studerer et amerikansk FDA-regulert medikamentprodukt
Nei
Studerer et amerikansk FDA-regulert enhetsprodukt
Nei
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