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AI as an Aid for Weekly Symptom Intake in Radiotherapy

NCT06525181 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 200

Last updated 2024-10-10

No results posted yet for this study

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.

Conditions

  • Radiotherapy Side Effect
  • Pelvic Cancer
  • Patient

Interventions

OTHER

Generative Artificial Intelligence

Gen AI assisted symptom intake summarization

OTHER

Standard weekly symptom intake

Standard weekly symptom intake performed by a physician

Sponsors & Collaborators

  • National Cancer Institute, Brazil

    collaborator UNKNOWN

  • jaide

    lead INDUSTRY

Study Design

Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-07-22
Primary Completion
2024-11-01
Completion
2024-12-15

Countries

  • Brazil

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06525181 on ClinicalTrials.gov