Research on the Development and Validation of Personalized Exercise Prescription System for Breast Cancer Patients Based on Large Language Models

August 11, 2026 updated by: 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.

Study Overview

Status

Not yet recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

40

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

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.

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Overall Quality Score of Exercise Prescriptions Based on a Five-Dimensional Expert Evaluation Framework
Time Frame: From enrollment to completion of prescription evaluation at 1 week
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.
From enrollment to completion of prescription evaluation at 1 week

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Subgroup-Specific Scientific Rationale and Safety Scores of Model-Generated Exercise Prescriptions
Time Frame: From enrollment to completion of prescription evaluation at 1 week
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.
From enrollment to completion of prescription evaluation at 1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 15, 2026

Primary Completion (Estimated)

July 1, 2027

Study Completion (Estimated)

December 31, 2027

Study Registration Dates

First Submitted

August 11, 2026

First Submitted That Met QC Criteria

August 11, 2026

First Posted (Actual)

August 17, 2026

Study Record Updates

Last Update Posted (Actual)

August 17, 2026

Last Update Submitted That Met QC Criteria

August 11, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SYSKY-2025-786-02

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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