Correction to: Graphing and reporting heterogeneous treatment effects through reference classes.
Journal article
Watson JA. and Holmes CC., (2020), Trials, 21
A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices.
Journal article
Watson JA. et al, (2020), PLoS genetics, 16
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.
Journal article
Cruz Rivera S. et al, (2020), The Lancet. Digital health, 2, e549 - e560
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.
Journal article
Liu X. et al, (2020), The Lancet. Digital health, 2, e537 - e548
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.
Journal article
Cruz Rivera S. et al, (2020), Nature medicine, 26, 1351 - 1363
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.
Journal article
Liu X. et al, (2020), Nature medicine, 26, 1364 - 1374
NRF2 metagene signature is a novel prognostic biomarker in colorectal cancer.
Journal article
O'Cathail SM. et al, (2020), Cancer genetics, 248-249, 1 - 10
Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis.
Journal article
Benedetto U. et al, (2020), The Journal of thoracic and cardiovascular surgery
On the marginal likelihood and cross-validation
Journal article
Fong E. and Holmes CC., (2020), Biometrika, 107, 489 - 496
Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study.
Journal article
Banerjee A. et al, (2020), Lancet (London, England), 395, 1715 - 1725
Graphing and reporting heterogeneous treatment effects through reference classes.
Journal article
Watson JA. and Holmes CC., (2020), Trials, 21
Testing for dependence on tree structures.
Journal article
Behr M. et al, (2020), Proceedings of the National Academy of Sciences of the United States of America
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness.
Journal article
Vollmer S. et al, (2020), BMJ (Clinical research ed.), 368
Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error.
Journal article
Watson JA. and Holmes CC., (2020), Trials, 21
A framework for adaptive mcmc targeting multimodal distributions
Journal article
Pompe E. et al, (2020), Annals of Statistics, 48, 2930 - 2952
Explicit regularisation in Gaussian noise injections
Conference paper
Camuto A. et al, (2020), Advances in Neural Information Processing Systems, 2020-December
Improving the quality of machine learning in health applications and clinical research
Journal article
Mateen BA. et al, (2020), Nature Machine Intelligence
Author Correction: Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed.
Journal article
CONSORT-AI and SPIRIT-AI Steering Group None., (2019), Nature medicine, 25
Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed.
Journal article
CONSORT-AI and SPIRIT-AI Steering Group None., (2019), Nature medicine, 25, 1467 - 1468