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Showing 1–9 of 9 results
Advanced filters: Author: Chris Harbron Clear advanced filters

  • Gathering big datasets has become an essential component of machine learning in many scientific areas, but it is unavoidable that some data values are missing. An important and growing effect that needs careful attention, especially when heterogeneous data sources are combined, is that of structured missingness, where data values are missing not at random, but with a specific structure.

    • Robin Mitra
    • Sarah F. McGough
    • Ben D. MacArthur
    Reviews
    Nature Machine Intelligence
    Volume: 5, P: 13-23

  • Artificial intelligence tools usually aim to maximize predictive accuracy, but personalized measures of uncertainty, using new techniques such as conformal prediction, are needed for clinical artificial intelligence to realize its potential and improve human health.

    • Christopher R. S. Banerji
    • Tapabrata Chakraborti
    • Ben D. MacArthur
    Comments & Opinion
    Nature Medicine
    Volume: 29, P: 2996-2998

  • AI tools are increasingly used for important decisions, but they can be uncertain about specific individuals or groups. Chakraborty et al. discuss the need for better methods to assess uncertainty in high-stakes applications such as healthcare and finance, and outline a set of main challenges to provide practical guidance for AI researchers.

    • Tapabrata Chakraborti
    • Christopher R. S. Banerji
    • Ben MacArthur
    Reviews
    Nature Machine Intelligence
    Volume: 7, P: 522-530

  • New statistical and machine learning techniques to understand, quantify and correct for the impact of biases in genomic data are emerging. The authors review how the choice of analytical methods used to process, analyse and interpret genomic data can influence genomic research, as well as existing methodological approaches to promote equity and fairness in genomics.

    • Brieuc Lehmann
    • Leandra Bräuninger
    • Chris Holmes
    Reviews
    Nature Reviews Genetics
    Volume: 26, P: 635-649

    • Anthony Baptista
    • Alessandro Barp
    • Christopher R. S. Banerji
    ResearchOpen Access
    Scientific Reports
    Volume: 14, P: 1-11