5 Matching Annotations
  1. Mar 2021
  2. www.nature.com www.nature.com
    Forecasting influenza-like illness trends in Cameroon using Google Search Data
    1
    1. zoe_ikeotuonye 25 Mar 2021

      Nsoesie, E. O., Oladeji, O., Abah, A. S. A., & Ndeffo-Mbah, M. L. (2021). Forecasting influenza-like illness trends in Cameroon using Google Search Data. Scientific Reports, 11(1), 6713. https://doi.org/10.1038/s41598-021-85987-9

      is:article lang:en computational science infectious disease influenza data Google research mortality pandemic disease infection digital data machine learning machine learning model
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    nature.com/articles/s41598-021-85987-9
  3. www.cam.ac.uk www.cam.ac.uk
    Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use
    1
    1. zoe_ikeotuonye 22 Mar 2021

      Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use. (2021, March 15). University of Cambridge. https://www.cam.ac.uk/research/news/machine-learning-models-for-diagnosing-covid-19-are-not-yet-suitable-for-clinical-use

      is:article lang:en machine learning diagnosing COVID-19 model systematic review medicine medical medical image research scientific method review peer review artificial intelligence imaging
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    cam.ac.uk/research/news/machine-learning-models-for-diagnosing-covid-19-are-not-yet-suitable-for-clinical-use
  4. Dec 2020
  5. psyarxiv.com psyarxiv.com
    Putting psychology to the test: Rethinking model evaluation through benchmarking and prediction
    1
    1. marta_radosevic 01 Dec 2020

      Rocca, R., & Yarkoni, T. (2020). Putting psychology to the test: Rethinking model evaluation through benchmarking and prediction. PsyArXiv. https://doi.org/10.31234/osf.io/e437b

      is:preprint lang:en psychology model evaluation benchmarking machine learning reliability modelling utility prediction
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    psyarxiv.com/e437b/
  6. Sep 2020
  7. psyarxiv.com psyarxiv.com
    Unifying recommendation and active learning for information filtering and recommender systems
    1
    1. katietaylor_99 07 Sep 2020

      Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.

      is:preprint lang:en active learning information filtering recommender system algorithms Internet AI artificial intelligence machine learning predictive accuracy recommendation accuracy exploration-exploitation tradeoff parameterized model cognitive science computer science experimental approach
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    psyarxiv.com/jqa83/
  8. Jun 2020
  9. arxiv.org arxiv.org
    Clustering - What Both Theoreticians and Practitioners are Doing Wrong
    1
    1. ErikStuchly 25 Jun 2020

      Ben-David, S. (2018). Clustering—What Both Theoreticians and Practitioners are Doing Wrong. ArXiv:1805.08838 [Cs, Stat]. http://arxiv.org/abs/1805.08838

      is:article lang:en cluster clustering tool machine learning unsupervised learning theory practice algorithm parameter computational task optimization model selection
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    arxiv.org/abs/1805.08838