- Sep 2021
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www.nature.com www.nature.com
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Lee, J. W., Su, Y., Baloni, P., Chen, D., Pavlovitch-Bedzyk, A. J., Yuan, D., Duvvuri, V. R., Ng, R. H., Choi, J., Xie, J., Zhang, R., Murray, K., Kornilov, S., Smith, B., Magis, A. T., Hoon, D. S. B., Hadlock, J. J., Goldman, J. D., Price, N. D., … Heath, J. R. (2021). Integrated analysis of plasma and single immune cells uncovers metabolic changes in individuals with COVID-19. Nature Biotechnology, 1–11. https://doi.org/10.1038/s41587-021-01020-4
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- Sep 2020
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www.thelancet.com www.thelancet.com
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Wilkinson, Jack, Kellyn F. Arnold, Eleanor J. Murray, Maarten van Smeden, Kareem Carr, Rachel Sippy, Marc de Kamps, et al. ‘Time to Reality Check the Promises of Machine Learning-Powered Precision Medicine’. The Lancet Digital Health 0, no. 0 (16 September 2020). https://doi.org/10.1016/S2589-7500(20)30200-4.
Tags
- personalised medical approach
- machine learning
- revolution
- improved diagnosis
- prediction of individual responses
- clinical science
- electronic health database
- challenges
- machine learning powered precision medicine
- collaboration
- lang:en
- clinical practice
- algorithmic complexity
- is:report
Annotators
URL
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- May 2020
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annals.org annals.org
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Restrepo, D., Armstrong, K. A., & Metlay, J. P. (2020). Annals Clinical Decision Making: Avoiding Cognitive Errors in Clinical Decision Making. Annals of Internal Medicine. https://doi.org/10.7326/M19-3692
Tags
- decision-making
- error
- misdiagnosis
- is:article
- cognitive
- morbidity
- therapeutic option
- clinical
- psychology
- diagnosis
- lang:en
Annotators
URL
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- Apr 2020
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Janiaud, P., Axfors, C., Saccilotto, R., & Hemkens, L. (2020). COVID-evidence: A living database of trials on interventions for COVID-19. https://doi.org/10.17605/OSF.IO/GEHFX
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