Evaluating the Efficacy and Safety of AI Localization Models in Multidisciplinary Team Care for NSCLC

Condition(s) studied

Investigational drug(s) / intervention(s)

Treat Regimen: The impact of artificial intelligence on clinicians' treatment plans

Study summary

The goal of this clinical trial is to evaluate the effectiveness and safety of a locally deployed artificial intelligence (AI) decision-support model in the multidisciplinary team (MDT) process for patients with non-small cell lung cancer (NSCLC).

The main questions it aims to answer :

What is the level of agreement between treatment recommendations generated by the AI model and those made by a traditional MDT? How often do clinicians modify their final treatment decision after reviewing the AI model's recommendation? Researchers will compare treatment plans from the traditional MDT (Arm 1), the AI model (Arm 2), and the clinician's final decision after reviewing the AI output (Arm 3) to assess consistency, decision modification rates, and clinical efficiency.

Participants will:

Have their clinical, imaging, and molecular data submitted to both the traditional MDT and the AI model for independent treatment recommendations Receive a final treatment plan determined by clinicians after reviewing both recommendations, with follow-up for safety and survival outcomes

Eligibility

Primary outcome measure(s)

• Consistency rate — Baseline(MDT 1 Day)
  Consistency rate between Option 1 and Option 2 (calculated using Kappa value). Consistency rate between Option 1 and Option 3 (decision modification rate).

Trial sites (1)

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