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Calibrating random forests for probability estimation.
Dankowski T, Ziegler A. Dankowski T, et al. Stat Med. 2016 Sep 30;35(22):3949-60. doi: 10.1002/sim.6959. Epub 2016 Apr 13. Stat Med. 2016. PMID: 27074747 Free PMC article.
Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for
Probabilities can be consistently estimated using random forests. It is, however, unclear how random f
An independently validated survival nomogram for lower-grade glioma.
Gittleman H, Sloan AE, Barnholtz-Sloan JS. Gittleman H, et al. Neuro Oncol. 2020 May 15;22(5):665-674. doi: 10.1093/neuonc/noz191. Neuro Oncol. 2020. PMID: 31621885 Free PMC article.
Survival was assessed using Cox proportional hazards regression, random survival forests, and recursive partitioning analysis, with adjustment for known prognostic factors. ...Factors that increased the probability of survival included grade II tumor, younger …
Survival was assessed using Cox proportional hazards regression, random survival forests, and recursive partitioning analysis, …
ABC random forests for Bayesian parameter inference.
Raynal L, Marin JM, Pudlo P, Ribatet M, Robert CP, Estoup A. Raynal L, et al. Bioinformatics. 2019 May 15;35(10):1720-1728. doi: 10.1093/bioinformatics/bty867. Bioinformatics. 2019. PMID: 30321307
The approach relies on the random forest (RF) methodology of Breiman (2001) applied in a (non-parametric) regression setting. ...When compared with earlier ABC solutions, this method offers significant gains in terms of robustness to the choice of the summary statis …
The approach relies on the random forest (RF) methodology of Breiman (2001) applied in a (non-parametric) regression setting. …
Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction.
Angraal S, Mortazavi BJ, Gupta A, Khera R, Ahmad T, Desai NR, Jacoby DL, Masoudi FA, Spertus JA, Krumholz HM. Angraal S, et al. JACC Heart Fail. 2020 Jan;8(1):12-21. doi: 10.1016/j.jchf.2019.06.013. Epub 2019 Oct 9. JACC Heart Fail. 2020. PMID: 31606361 Free article.
METHODS: The following 5 methods: logistic regression with a forward selection of variables; logistic regression with a lasso regularization for variable selection; random forest (RF); gradient descent boosting; and support vector machine, were used to train models …
METHODS: The following 5 methods: logistic regression with a forward selection of variables; logistic regression with a lasso regularization …
Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
Deist TM, Dankers FJWM, Valdes G, Wijsman R, Hsu IC, Oberije C, Lustberg T, van Soest J, Hoebers F, Jochems A, El Naqa I, Wee L, Morin O, Raleigh DR, Bots W, Kaanders JH, Belderbos J, Kwint M, Solberg T, Monshouwer R, Bussink J, Dekker A, Lambin P. Deist TM, et al. Med Phys. 2018 Jul;45(7):3449-3459. doi: 10.1002/mp.12967. Epub 2018 Jun 13. Med Phys. 2018. PMID: 29763967 Free PMC article.
General Machine learning literature provides evidence in favor of some classifier families (random forest, support vector machine, gradient boosting) in terms of classification performance. ...CONCLUSION: Random forest and elastic net logistic regressi …
General Machine learning literature provides evidence in favor of some classifier families (random forest, support vector mach …
Machine Learning and Statistical Models to Predict Postpartum Hemorrhage.
Venkatesh KK, Strauss RA, Grotegut CA, Heine RP, Chescheir NC, Stringer JSA, Stamilio DM, Menard KM, Jelovsek JE. Venkatesh KK, et al. Obstet Gynecol. 2020 Apr;135(4):935-944. doi: 10.1097/AOG.0000000000003759. Obstet Gynecol. 2020. PMID: 32168227 Free PMC article.
METHODS: Predictive models were constructed and compared using data from 10 of 12 sites in the U.S. Consortium for Safe Labor Study (2002-2008) that consistently reported estimated blood loss at delivery. ...We used logistic regression with and without lasso regular …
METHODS: Predictive models were constructed and compared using data from 10 of 12 sites in the U.S. Consortium for Safe Labor Study ( …
External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.
Snell KIE, Allotey J, Smuk M, Hooper R, Chan C, Ahmed A, Chappell LC, Von Dadelszen P, Green M, Kenny L, Khalil A, Khan KS, Mol BW, Myers J, Poston L, Thilaganathan B, Staff AC, Smith GCS, Ganzevoort W, Laivuori H, Odibo AO, Arenas Ramírez J, Kingdom J, Daskalakis G, Farrar D, Baschat AA, Seed PT, Prefumo F, da Silva Costa F, Groen H, Audibert F, Masse J, Skråstad RB, Salvesen KÅ, Haavaldsen C, Nagata C, Rumbold AR, Heinonen S, Askie LM, Smits LJM, Vinter CA, Magnus P, Eero K, Villa PM, Jenum AK, Andersen LB, Norman JE, Ohkuchi A, Eskild A, Bhattacharya S, McAuliffe FM, Galindo A, Herraiz I, Carbillon L, Klipstein-Grobusch K, Yeo SA, Browne JL, Moons KGM, Riley RD, Thangaratinam S; IPPIC Collaborative Network. Snell KIE, et al. BMC Med. 2020 Nov 2;18(1):302. doi: 10.1186/s12916-020-01766-9. BMC Med. 2020. PMID: 33131506 Free PMC article.
Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. ...There was large between-study heterogeneity in each model's calibration-in-the-large, suggest …
Performance measures were estimated separately in each available study and then, where possible, combined across studies in a rand
Random forest for prediction of contrast-induced nephropathy following coronary angiography.
Liu Y, Chen S, Ye J, Xian Y, Wang X, Xuan J, Tan N, Li Q, Chen J, Ni Z. Liu Y, et al. Int J Cardiovasc Imaging. 2020 Jun;36(6):983-991. doi: 10.1007/s10554-019-01730-6. Epub 2020 Apr 13. Int J Cardiovasc Imaging. 2020. PMID: 32285318
A total of 3469 patients undergoing PCI/CAG between January 2010 and December 2013 were randomly divided into a training (n = 2428, 70%) and validation data-sets (n = 1041, 30%). Random forest full models were developed using 40 pre-procedural variables, of which 13 …
A total of 3469 patients undergoing PCI/CAG between January 2010 and December 2013 were randomly divided into a training (n = 2428, 70%) and …
Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.
Mervin LH, Afzal AM, Engkvist O, Bender A. Mervin LH, et al. J Chem Inf Model. 2020 Oct 26;60(10):4546-4559. doi: 10.1021/acs.jcim.0c00476. Epub 2020 Sep 21. J Chem Inf Model. 2020. PMID: 32865408
In comparison, the PS and IR methods can actually degrade the assigned probability estimates, particularly for the RF for SSS and during L20SO. Sphere exclusion, a method to sample additional (putative) inactive compounds, was shown to inflate the overall Brier scor …
In comparison, the PS and IR methods can actually degrade the assigned probability estimates, particularly for the RF for SSS …
Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.
Maros ME, Capper D, Jones DTW, Hovestadt V, von Deimling A, Pfister SM, Benner A, Zucknick M, Sill M. Maros ME, et al. Nat Protoc. 2020 Feb;15(2):479-512. doi: 10.1038/s41596-019-0251-6. Epub 2020 Jan 13. Nat Protoc. 2020. PMID: 31932775
Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly multiclass classification tasks are still lacking. To support this choice, we evaluated well-established machine learning (ML) classifie …
Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically hig …
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