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. 2022 Mar 16;12(3):722. doi: 10.3390/diagnostics12030722

Table A4.

Characteristics of mobile and could-based CVD systems.

C0 C1 C2 C3 C4 C5 C6 C7 C8
SN Authors/Citations ST Year Journal DS Diseases FDA SV Comparator
1 Buss et al. [197] SR 2020 JMIR 7 ED CVD, DIA 🗶 🗶 No (i.e., standard care),
await list control, intervention
2 Villarreal et al. [198] SR 2020 AIF 44 CVD 🗶 🗶 CVD, No CVD
3 Xiao et al. [199] R 2017 TM 151 CVD 🗶 🗶 CVD, No CVD
4 Saba et al. [200] R 2018 IHJ 100 CVD 🗶 🗸 CVD, No CVD
5 Lillo-Castellano et al. [208] R 2015 JBHI 6848 CVD 🗸 🗸 CVD, No CVD
6 Huda et al. [201] R 2020 TENSYMP BIHAD CVD 🗶 🗸 Normal ECG, Abnormal ECG
7 Sakellarios et al. [209] R 2018 EMBC 236 CAD 🗶 🗸 No CAD, OCAD, Non-OCAD
8 Singh et al. [202] R 2019 IEEEc 2 CVDa 🗶 🗸 Arrhythmia, CVD
9 Spanakis et al. [203] R 2020 EMBC 🗶 CHF 🗶 🗸 CHF, No CHF
10 Paredes et al. [204] R 2018 BIBM 1600 MI, CVD 🗶 🗸 Acute MI, No MI
11 Freyer et al. [205] R 2021 AJH 🗶 AF 🗶 🗸 AF, No AF
12 Giansanti et al. [206] S 2021 mHealth 🗶 CVD 🗶 🗶 Use of AI, non-use of AI
13 Park et al. [207] R 2014 IEEEa 🗶 Arrhythmia 🗶 🗶 Arrhythmia, CVD
SN Authors/Citations Non ML/ML Cloud Mob Sea DE Analysis # O OT # C Classifier
1 Buss et al. [197] Non-ML 🗶 🗸 🗸 🗸 🗸 2 Dia, CVD 3 🗶
2 Villarreal et al. [198] Non-ML 🗸 🗸 🗸 🗸 🗸 1 CVD 2 🗶
3 Xiao et al. [199] Non-ML 🗶 🗸 🗸 🗸 🗸 1 CVD 2 🗶
4 Saba et al. [200] Non-ML 🗸 🗸 🗸 🗸 🗸 1 CVD 2 🗶
5 Lillo-Castellano et al. [208] ML 🗸 🗶 🗸 🗸 🗸 1 CVD 2 k-NN
6 Huda et al. [201] ML, DL 🗸 🗸 🗸 🗸 🗸 1 Arrhythmia 2 SVM, CNN
7 Sakellarios et al. [209] ML 🗸 🗶 🗸 🗸 🗸 1 CVD 3 SVM
8 Singh et al. [202] DL 🗸 🗸 🗸 🗸 🗸 1 CVDa 2 CNN
9 Spanakis et al. [203] IoT 🗸 🗸 🗸 🗸 🗸 1 CHF 2 🗶
10 Paredes et al. [204] CI 🗶 🗸 🗸 🗸 🗸 2 CVD, MI 2 Bayesian
11 Freyer et al. [205] Non-ML 🗸 🗸 🗸 🗸 🗸 1 AF 2 🗶
12 Giansanti et al. [206] AI 🗸 🗸 🗸 🗸 🗸 1 CVD 2 🗶
13 Park et al. [207] ML 🗶 🗸 🗸 🗸 🗸 1 Arrhythmia 2 DT, RF
C0 C19 C20 C21 C22 C23 C24 C25 C26 C27 C28 C29
SN Authors/Citations CV Protocol # PE SEN SPEC Acc Pre F1 S PV SS ROC
1 Buss et al. [197] 🗶 🗶 0 🗶 🗶 🗶 🗶 🗶 🗶 🗶 🗶
2 Villarreal et al. [198] 🗶 🗶 0 🗶 🗶 🗶 🗶 🗶 🗶 🗶 🗶
3 Xiao et al. [199] 🗶 🗶 1 🗶 🗶 🗶 🗶 🗶 🗶 2.87 🗶
4 Saba et al. [200] 🗸 🗶 1 🗶 🗶 🗶 🗶 🗶 🗶 🗶 1
5 Lillo-Castellano et al. [208] 🗸 K 1 🗶 🗶 90 🗶 🗶 🗶 🗶 🗶
6 Huda et al. [201] 🗸 🗶 1 🗶 🗶 96 🗶 🗶 🗶 🗶 🗶
7 Sakellarios et al. [209] 🗸 🗶 3 44 98.7 85.1 🗶 🗶 🗶 🗶 🗶
8 Singh et al. [202] 🗶 🗶 1 🗶 🗶 97 🗶 🗶 🗶 🗶 🗶
9 Spanakis et al. [203] 🗶 🗶 1 🗶 🗶 1 🗶 🗶 🗶 🗶 🗶
10 Paredes et al. [204] 🗸 🗶 0 🗶 🗶 🗶 🗶 🗶 🗶 🗶 🗶
11 Freyer et al. [205] 🗸 🗶 1 🗶 🗶 1 🗶 🗶 🗶 🗶 🗶
12 Giansanti et al. [206] 🗸 🗶 0 🗶 🗶 🗶 🗶 🗶 🗶 🗶 🗶
13 Park et al. [207] 🗸 🗶 3 1 1 1 🗶 🗶 🗶 🗶 🗶

SN: Serial number; CV: Cross validation; SEN: Sensitivity; SPEC: Specificity; Acc: Accuracy; Pre: Precision; F1 S: F1 Score; PV: p-value; SS: Silberg score. DE: Data extraction; OT: Outcome types; C: Comparators; O: Outcomes; CI: Computational intelligence; CHF: Congestive heart failure; CVDa: CVD Auscultation; Dia: Diabetes; MI: Myocardial infarction; Mob: Mobile; Sea: Scientific validation; # O: Number of outcomes; # C: Number of classes. DS: Data size; BIHAD: MIT-BIH Arrhythmia Database; IEEEc: IEEE connect; AF: Atrial fibrillation; R: Research; SR: Systemic review; ST: Study type; IHJ: Indian Heart Journal; AIF: AI Foundation; TM: Telemedicine; IEEEa: IEEE-ACAINA; SV: Scientific validation; OCAD: Obstructive CAD; NonOCAD: Non-obstructive CAD.