AI as an Aid for Weekly Symptom Intake in Radiotherapy

Recruiting now · Not applicable

Conditions studied: Radiotherapy Side Effect, Pelvic Cancer, Patient

In brief

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.

Key facts

Study ID

NCT06525181

Run by

jaide

People needed

200

Starts

2024-07-22

Expected to finish

2024-12-15

Last updated by the study team

2024-10-10

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• All patients undergoing radiotherapy in the pelvic region.

You may not qualify if…

• Cases of pelvic reirradiation or operated cases.

Where it is running

• Instituto Nacional de Câncer José Alencar Gomes da Silva - INCA — Rio de Janeiro, Brazil (enrolling)

Full record on ClinicalTrials.gov

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