This study examines a GPT-4-based virtual assistant developed to aid oncologists in therapeutic choices for metastatic breast cancer, aiming to evaluate the system's accuracy and interpretability in real-life patient care. A cohort of 43 metastatic breast cancer patients from ARNAS Civico Hospital in Palermo, Italy, was included. Patient data— such as comorbidities, disease progression, and lab results—were analyzed, with therapeutic recommendations generated by the AI model compared to established guidelines. Three physicians independently rated the model’s interpretability on a scale from 1 to 5. The virtual assistant achieved a high concordance rate of 91% with AIOM guidelines. The interpretability of the model’s recommendations received an average score of 4.7/5 from the reviewing physicians. The GPT-4-based virtual assistant shows strong potential as a reliable, transparent tool to support oncologists in therapeutic decision-making for metastatic breast cancer.

Therapeutic Decision-Making in Breast Cancer: The Contribution of Artificial Intelligence

Campione Marina
Writing – Original Draft Preparation
;
Aiello Fabio;
2024-01-01

Abstract

This study examines a GPT-4-based virtual assistant developed to aid oncologists in therapeutic choices for metastatic breast cancer, aiming to evaluate the system's accuracy and interpretability in real-life patient care. A cohort of 43 metastatic breast cancer patients from ARNAS Civico Hospital in Palermo, Italy, was included. Patient data— such as comorbidities, disease progression, and lab results—were analyzed, with therapeutic recommendations generated by the AI model compared to established guidelines. Three physicians independently rated the model’s interpretability on a scale from 1 to 5. The virtual assistant achieved a high concordance rate of 91% with AIOM guidelines. The interpretability of the model’s recommendations received an average score of 4.7/5 from the reviewing physicians. The GPT-4-based virtual assistant shows strong potential as a reliable, transparent tool to support oncologists in therapeutic decision-making for metastatic breast cancer.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11387/185053
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