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AI as an Aid for Weekly Symptom Intake in Radiotherapy
Sponsor: jaide
Summary
The study investigates the use of artificial intelligence (AI) and large language models (LLMs) to enhance the efficiency and accuracy of weekly treatment consultations (OTVs) in radiotherapy. It hypothesizes that an AI-enabled symptom summary tool will match traditional medical review methods in accuracy while saving time. The study includes patients undergoing pelvic radiotherapy and excludes those with pelvic reirradiation or who have undergone surgery. Patients will receive both standard and AI-assisted weekly consultations, with AI summaries generated using the OpenAI GPT-4 API. Blinded oncologists will compare the accuracy and quality of the AI-generated and doctor-generated summaries, while patients and doctors will rate these summaries. The primary objective is to evaluate the accuracy and time efficiency of AI-assisted symptom summaries compared to traditional methods.
Official title: Evaluation of AI-Enhanced Symptom Summarization in Weekly Radiotherapy Consultations: A Comparative Study
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
200
Start Date
2024-07-22
Completion Date
2024-12-15
Last Updated
2024-10-10
Healthy Volunteers
No
Interventions
Generative Artificial Intelligence
Gen AI assisted symptom intake summarization
Standard weekly symptom intake
Standard weekly symptom intake performed by a physician
Locations (1)
Instituto Nacional de Câncer José Alencar Gomes da Silva - INCA
Rio de Janeiro, Brazil