Multi-omics AI model boosts preterm birth prediction accuracy to nearly 90%
Peer-Reviewed Publication
Updates every hour. Last Updated: 12-Nov-2025 00:11 ET (12-Nov-2025 05:11 GMT/UTC)
A recent study developed a highly accurate risk prediction framework for preterm birth (PTB) that could broaden the potential of AI-driven multi-omics applications in precision obstetrics and biomedical research.
The model, deeply integrating genomics, transcriptomics, and large language models (LLMs) for the first time for PTB risk prediction, has shown its effectiveness and clinical application prospects.
The research was conducted by a collaborative team led by BGI Genomics, together with Professor Huang Hefeng's team, Shenzhen Longgang Maternal and Child Health Hospital, Fujian Maternity and Child Health Hospital, and OxTium Technology. The research was published in npj Digital Medicine on August 20th.
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