Garibaldi JM - Search Results

1

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Weng SF, Reps J, Kai J, Garibaldi JM, Qureshi N. Weng SF, et al. Among authors: garibaldi jm. PLoS One. 2017 Apr 4;12(4):e0174944. doi: 10.1371/journal.pone.0174944. eCollection 2017. PLoS One. 2017. PMID: 28376093 Free PMC article.

2

A supervised adverse drug reaction signalling framework imitating Bradford Hill's causality considerations.

Reps JM, Garibaldi JM, Aickelin U, Gibson JE, Hubbard RB. Reps JM, et al. Among authors: garibaldi jm. J Biomed Inform. 2015 Aug;56:356-68. doi: 10.1016/j.jbi.2015.06.011. Epub 2015 Jun 24. J Biomed Inform. 2015. PMID: 26116429 Free article.

3

A signalome screening approach in the autoinflammatory disease TNF receptor associated periodic syndrome (TRAPS) highlights the anti-inflammatory properties of drugs for repurposing.

Todd I, Negm OH, Reps J, Radford P, Figueredo G, McDermott EM, Drewe E, Powell RJ, Bainbridge S, Hamed M, Crouch S, Garibaldi J, St-Gallay S, Fairclough LC, Tighe PJ. Todd I, et al. Pharmacol Res. 2017 Nov;125(Pt B):188-200. doi: 10.1016/j.phrs.2017.08.012. Epub 2017 Aug 30. Pharmacol Res. 2017. PMID: 28860008

4

Signalling paediatric side effects using an ensemble of simple study designs.

Reps JM, Garibaldi JM, Aickelin U, Soria D, Gibson JE, Hubbard RB. Reps JM, et al. Among authors: garibaldi jm. Drug Saf. 2014 Mar;37(3):163-70. doi: 10.1007/s40264-014-0137-z. Drug Saf. 2014. PMID: 24550103

5

Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.

Chernbumroong S, Johnson J, Gupta N, Miller S, McCormack FX, Garibaldi JM, Johnson SR. Chernbumroong S, et al. Among authors: garibaldi jm. Eur Respir J. 2021 Jun 4;57(6):2003036. doi: 10.1183/13993003.03036-2020. Print 2021 Jun. Eur Respir J. 2021. PMID: 33303533 Free article.

6

A novel semisupervised algorithm for rare prescription side effect discovery.

Reps JM, Garibaldi JM, Aickelin U, Soria D, Gibson JE, Hubbard RB. Reps JM, et al. Among authors: garibaldi jm. IEEE J Biomed Health Inform. 2014 Mar;18(2):537-47. doi: 10.1109/JBHI.2013.2281505. IEEE J Biomed Health Inform. 2014. PMID: 24043412 Free article.

7

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

Glaab E, Bacardit J, Garibaldi JM, Krasnogor N. Glaab E, et al. Among authors: garibaldi jm. PLoS One. 2012;7(7):e39932. doi: 10.1371/journal.pone.0039932. Epub 2012 Jul 11. PLoS One. 2012. PMID: 22808075 Free PMC article.

8

A hybrid model for automatic identification of risk factors for heart disease.

Yang H, Garibaldi JM. Yang H, et al. Among authors: garibaldi jm. J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S171-S182. doi: 10.1016/j.jbi.2015.09.006. Epub 2015 Sep 12. J Biomed Inform. 2015. PMID: 26375492 Free PMC article.

9

A new accuracy measure based on bounded relative error for time series forecasting.

Chen C, Twycross J, Garibaldi JM. Chen C, et al. Among authors: garibaldi jm. PLoS One. 2017 Mar 24;12(3):e0174202. doi: 10.1371/journal.pone.0174202. eCollection 2017. PLoS One. 2017. PMID: 28339480 Free PMC article.

10

MysiRNA: improving siRNA efficacy prediction using a machine-learning model combining multi-tools and whole stacking energy (ΔG).

Mysara M, Elhefnawi M, Garibaldi JM. Mysara M, et al. Among authors: garibaldi jm. J Biomed Inform. 2012 Jun;45(3):528-34. doi: 10.1016/j.jbi.2012.02.005. Epub 2012 Feb 25. J Biomed Inform. 2012. PMID: 22388012 Free article.

Save citations to file

Email citations

Send citations to clipboard

Add to Collections

Add to My Bibliography

Create a file for external citation management software

Your saved search

Your RSS Feed

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Article Language

Species

Sex

Age

Other

59 results

Search Page

Filters