Applied Bionics and Biomechanics

Review Article

Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review

Table 3

Studies included in the radiomics-section analysis and AI methods applied.
ReferencesMethod of data analysisAI approaches
Huang et al. [44]—Convolutional neural networks
Sanchez-Martinez et al. [46]—Machine learning, clustering
Madani et al. [47]—Convolutional neural networks
Soto et al. [48]—Deep learning
Duffy et al. [49]—Deep learning
Yuan et al. [50]—Deep learning
Liu et al. [51]—Deep learning
Kay et al. [54]—Machine learning, logistic regression
Hu et al. [60]—Logistic regression
Gupta et al. [61]—Deep neural network
Atkov et al. [62]—Deep neural network
Lin et al. [64]—Machine learning
Coenen et al. [65]—Machine learning
Al’Aref et al. [66]—Machine learning
von Knebel Doeberitz et al. [68]—Deep learning
Lee et al. [70]—Machine learning
Bajaj et al. [71]—Machine learning
Amato et al. [72]—Unsupervised machine learning
Oikonomou et al. [74]—Machine learning
Commandeur et al. [75]—Deep learning
Eisenberg [76]—Deep learning
Chen et al. [78]—Unsupervised machine learning
Wu et al. [79]—Deep neural networks
Antonopoulos et al. [80]—Machine learning
Sengupta et al. [81]—Machine learning
Sparapani et al. [82]—Bayesian additive regression trees
Ma et al. [83]—Machine learning
Durmaz et al. [84]—Machine learning
Laudicella et al. [86]—Deep neural networks
Nakajima et al. [87]—Deep neural networks
Hu et al. [88]—Machine learning
Betancur et al. [89]—Deep learning
Betancur et al. [90]—Machine learning
Arsanjani et al. [92]—Machine learning
Lin et al. [93]—Machine learning
Baumann et al. [94]—Machine learning
Suinesiaputra et al. [95]—Deep neural networks
Lossnitzer et al. [96]—Machine learning
Lossnitzer et al. [97]—Machine learning
Lee et al. [70]SPSSMachine learning (binary class L2 penalized logistic regression, deep neural networks, random forest, AdaBoost, CatBoost, and support vector machine)
Ji et al. [98]SPSSDeep learning