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Artificial intelligence uses multi-omic data to predict pancreatic cancer outcomes

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We applied an artificial intelligence (AI) approach to a dataset of clinical and advanced multi-omic molecular features from patients with pancreatic adenocarcinoma to predict survival. The results reveal a tumor-type-agnostic platform that can identify parsimonious and robust clinical prediction biomarkers, catalyzing the vision to democratize precision oncology worldwide.

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Fig. 1: The Molecular Twin platform.

References

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a summary of: Osipov, A. et al. The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients. Nat. Cancer https://doi.org/10.1038/s43018-023-00697-7 (2024).

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Artificial intelligence uses multi-omic data to predict pancreatic cancer outcomes. Nat Cancer 5, 226–227 (2024). https://doi.org/10.1038/s43018-023-00698-6

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  • DOI: https://doi.org/10.1038/s43018-023-00698-6

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