Authors: M. Jaleed Khan, Ioana Duta, Beth Albert, William Cooke, Manu Vatish, Gabriel Davis Jones
Published on: April 11, 2024
Impact Score: 8.2
Arxiv code: Arxiv:2404.08024
Summary
- What is new: Introduction of the Oxford Maternity (OxMat) dataset, the largest curated dataset of cardiotocography (CTG) recordings combined with extensive clinical data for both mothers and babies.
- Why this is important: The advancement of AI in obstetric care is hindered by the lack of large, high-quality datasets suitable for machine learning.
- What the research proposes: The OxMat dataset provides over 177,211 unique CTG recordings from 51,036 pregnancies, along with over 200 clinical variables, addressing the gap in comprehensive women’s health data for AI applications.
- Results: The dataset’s vast size and detailed clinical variables make it an ideal resource for developing and testing AI algorithms aimed at improving maternal and fetal health outcomes, especially during the antepartum period.
Technical Details
Technological frameworks used: nan
Models used: nan
Data used: Oxford Maternity (OxMat) dataset with over 177,211 CTG recordings and 200+ clinical variables
Potential Impact
Healthcare providers and companies specializing in prenatal care technology could benefit significantly. AI software developers and data analytics firms focusing on healthcare applications may also find new opportunities.
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