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Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Conditions: Breast Cancer, Exercise and Recovery
Countries: China
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.
Sex: ALL
Age: 18 Years to 75 Years
Healthy volunteers: No
Study type: OBSERVATIONAL
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.
- Guangzhou, Guangdong, China