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Table 2 Different algorithms used in trauma study topics

From: Artificial intelligence and machine learning for hemorrhagic trauma care

Study topic

Category

Method in search

References

Different outcomes in trauma

Regression

LR

[34, 37, 41, 62,63,64,65,66,67,68,69,70,71,72]

Network

DNN, ANN, MLP, RBFN, Predictive Hierarchical Network, Polynomial NN, RSNNS

[27, 36, 37, 41, 63,64,65,66,67,68, 70, 71, 73,74,75,76,77,78,79,80]

Tree

CART, DT, RF, Recursive Partitioning Algorithm, OCT, Bayesian DT, unpruned C4.5 tree (J48), Archetypal DT

[27, 29, 30, 37, 41, 63, 67, 68, 70, 72, 81,82,83,84,85]

Kernel

SVM, SMO, Polynomial Kernel, SVM Radial

[29, 37, 63, 66, 71, 72, 81]

Ensemble

SuperLearner

[86]

Boosting

XGBoost, Gradient Boost

[32,33,34,35]

Other

LDA, ER, FIS, Inference methodology

[27, 28, 63, 66, 72, 81, 87]

Bayesian

GNB, NB, BBN

[27, 37, 69, 72, 82, 84, 88, 89]

Unmentioned/commercial ML algorithm, novel scoring systems

Deep-FLAIM, UKTRISS, TOP, 4TDS, EDI

[27, 31, 36, 61, 90, 91]

Classification

KNN, Maximum a Posteriori

[27, 37, 72, 84]

Risk assessment

Regression

LR, MLR

[39, 40, 42, 92,93,94,95,96]

Network

ANN, MLP, DNN, Dirichlet DNN

[38, 40, 42, 44, 93, 97, 98]

Tree

RF, DT, Boosted Tree

[40, 42, 43, 92, 95, 96, 98, 99]

Kernel

SVM, SVMR

[39, 95, 97, 99]

Bayesian

BBN, NB

[96, 98]

Boosting

XGBoost, Adaboost

[94, 97, 98, 100]

Ensemble

Bagging

[97]

Other

Generalized Linear Model, LDA

[99, 101]

Classification

KNN

[97]

Unmentioned/commercial ML algorithm, novel scoring systems

CRI, MGAP

[45, 102]

Transfusion

Network

NN

[49, 60, 103]

Kernel

SVM

[49]

Boosting

XGBoost

[48, 49]

Tree

Classification and regression tree, Recursive partitioning analysis

[48, 49, 104, 105]

Regression

Logistic regression

[48, 49, 106]

Unmentioned ML algorithm, commercial ML software, novel scoring systems

CRI, MASH, BRI

[47, 52, 107, 108]

Hemorrhage detection

Network

Multi-scale attentional network

[59]

Ensemble

Ensemble classifier

[109]

Regression

Poisson regression

[110]

Kernel

SVM

[56]

Unmentioned/commercial ML algorithm, novel scoring systems

BRI

[111]

Other

Linear/non-linear density model, NLP Linear Classifier

[51, 53, 112]

Coagulopathy

Regression

LR

[113]

Tree

DT, RF

[58, 113, 114]

Bayesian

BN

[57]

Unmentioned/commercial ML algorithm, novel scoring systems

Caprini RAM

[113]

  1. ANN artificial neural network, BBN bayesian belief network, BN bayesian network, BRI bleeding risk index, CART classification and regression tree, CRI critical reserve index, DNN deep neural network, DT decision tree, ER evidential reasoning, FIS fuzzy inference system, LDA linear discriminant analysis, LR logistic regression, MASH military acute severe haemorrhage, MGAP Mechanism, Glasgow coma scale, Age, and Arterial Pressure, MLP multi-layer perceptron, MLR multi-linear regression, NB Naïve bayes, NLP natural language processing, NN neural network, OCT octree method, RAM risk assessment model, RBFN radial basis function network, RF random forest, RSNNS stuttgart neural network simulator, SMO sequential minimal optimization, SVM support vector machines, TOP trauma outcome predictor, TSM trauma severity model, UKTRISS United Kingdom Trauma and Injury Severity Score