Feb. 9, 2024, 5:44 a.m. | Soroosh Tayebi Arasteh Tianyu Han Mahshad Lotfinia Christiane Kuhl Jakob Nikolas Kather Daniel Truhn S

cs.LG updates on arXiv.org arxiv.org

A knowledge gap persists between machine learning (ML) developers (e.g., data scientists) and practitioners (e.g., clinicians), hampering the full utilization of ML for clinical data analysis. We investigated the potential of the ChatGPT Advanced Data Analysis (ADA), an extension of GPT-4, to bridge this gap and perform ML analyses efficiently. Real-world clinical datasets and study details from large trials across various medical specialties were presented to ChatGPT ADA without specific guidance. ChatGPT ADA autonomously developed state-of-the-art ML models based on …

ada advanced analysis automated automated machine learning bridge chatgpt clinical clinicians cs.ai cs.cl cs.lg data data analysis data scientists developers extension gap gpt gpt-4 knowledge language language models large language large language models machine machine learning scientists studies

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