E10   |  13 min   |   Latest   |  Publication Source    Podcast based on: Javanmard Z, Zarean Shahraki S, Safari K, Omidi A, Raoufi S, Rajabi M, Akbari ME and Aria M (2025) Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis. Front. Oncol. 14:1420328. doi: 10.3389/fonc.2024.1420328https://doi.org/10.3389/fonc.2024.1420328Type: Review  |  Publication date: Jan 7, 2025 Summary: This systematic review and meta-analysis assesses the use of artificial intelligence (AI) and machine learning (ML) algorithms in predicting breast cancer survival. The study examined 32 articles, finding a mean validation accuracy of 89.73% across various ML methods, with hybrid models showing the highest accuracy. A key limitation highlighted was the prevalent use of internal validation, hindering the generalisability of the models. The research suggests significant potential for AI in breast cancer prediction but emphasises the need for rigorous external validation and improved data handling in future studies to ensure reliable clinical application. Keywords: breast cancer, survival prediction, machine learning, deep learning, clinical data, systematic review, meta-analysis Disclaimer: The content of this podcast is a summary and discussion of the original publication and does not represent the views of the authors or journal. The information shared here is intended for educational purposes only and does not constitute clinical advice or recommendations. It also uses AI-assisted summaries of the original work and may or may not contain innacuracies so we encourage listeners to consult the original publication for complete details.