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For: Krittanawong C, Rogers AJ, Johnson KW, Wang Z, Turakhia MP, Halperin JL, Narayan SM. Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management. Nat Rev Cardiol 2021;18:75-91. [PMID: 33037325 DOI: 10.1038/s41569-020-00445-9] [Cited by in Crossref: 10] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Ha ACT, Doumouras BS, Wang CN, Tranmer J, Lee DS. Prediction of sudden cardiac arrest in the general population: Review of traditional and emerging risk factors. Can J Cardiol 2022:S0828-282X(22)00050-2. [PMID: 35041932 DOI: 10.1016/j.cjca.2022.01.007] [Reference Citation Analysis]
2 Naseri Jahfari A, Tax D, Reinders M, van der Bilt I. Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View. JMIR Med Inform 2022;10:e29434. [PMID: 35044316 DOI: 10.2196/29434] [Reference Citation Analysis]
3 Safabakhsh S, Du D, Liew J, Parker J, Mcilroy C, Khasanova E, Indraratna P, Blanke P, Leipsic J, Andrade JG, Bennett MT, Hawkins NM, Chakrabarti S, Yeung J, Deyell MW, Krahn AD, Moss R, Ong K, Laksman Z. Bluetooth-enabled implantable cardiac monitors and two-way smartphone communication for patients with hypertrophic cardiomyopathy. CJC Open 2021. [DOI: 10.1016/j.cjco.2021.10.010] [Reference Citation Analysis]
4 Fang Y, Zou Y, Xu J, Chen G, Zhou Y, Deng W, Zhao X, Roustaei M, Hsiai TK, Chen J. Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor. Adv Mater 2021;33:e2104178. [PMID: 34467585 DOI: 10.1002/adma.202104178] [Cited by in Crossref: 35] [Cited by in F6Publishing: 29] [Article Influence: 35.0] [Reference Citation Analysis]
5 Nagarajan VD, Lee SL, Robertus JL, Nienaber CA, Trayanova NA, Ernst S. Artificial intelligence in the diagnosis and management of arrhythmias. Eur Heart J 2021:ehab544. [PMID: 34392353 DOI: 10.1093/eurheartj/ehab544] [Reference Citation Analysis]
6 Siontis KC, Friedman PA. The Role of Artificial Intelligence in Arrhythmia Monitoring. Card Electrophysiol Clin 2021;13:543-54. [PMID: 34330380 DOI: 10.1016/j.ccep.2021.04.011] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Woo JH, Kim EC, Kim SM. The Current Status of Breakthrough Devices Designation in the United States and Innovative Medical Devices Designation in Korea for Digital Health Software. Expert Rev Med Devices 2022. [PMID: 35255755 DOI: 10.1080/17434440.2022.2051479] [Reference Citation Analysis]
8 Zhang K, Wang J, Liu T, Luo Y, Loh XJ, Chen X. Machine Learning-Reinforced Noninvasive Biosensors for Healthcare. Adv Healthc Mater 2021;10:e2100734. [PMID: 34165240 DOI: 10.1002/adhm.202100734] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 9.0] [Reference Citation Analysis]
9 Kennel PJ, Rosenblum H, Axsom KM, Alishetti S, Brener M, Horn E, Kirtane AJ, Lin E, Griffin JM, Maurer MS, Burkhoff D, Sayer G, Uriel N. Remote Cardiac Monitoring in Patients With Heart Failure: A Review. JAMA Cardiol 2021. [PMID: 34964805 DOI: 10.1001/jamacardio.2021.5090] [Reference Citation Analysis]
10 Bodington R, Kassianides X, Bhandari S. Point-of-care testing technologies for the home in chronic kidney disease: a narrative review. Clin Kidney J 2021;14:2316-31. [PMID: 34751234 DOI: 10.1093/ckj/sfab080] [Reference Citation Analysis]
11 Ijaz SH, Shah SP, Majithia A. Implantable devices for heart failure monitoring. Prog Cardiovasc Dis 2021:S0033-0620(21)00130-4. [PMID: 34838788 DOI: 10.1016/j.pcad.2021.11.011] [Reference Citation Analysis]
12 Laad M, Kotecha K, Patil K, Pise R. Cardiac Diagnosis with Machine Learning: A Paradigm Shift in Cardiac Care. Applied Artificial Intelligence. [DOI: 10.1080/08839514.2022.2031816] [Reference Citation Analysis]
13 Rhodes CJ, Sweatt AJ, Maron BA. Harnessing Big Data to Advance Treatment and Understanding of Pulmonary Hypertension. Circ Res 2022;130:1423-44. [PMID: 35482840 DOI: 10.1161/CIRCRESAHA.121.319969] [Reference Citation Analysis]
14 Alsabah M, Naser MA, Mahmmod BM, Abdulhussain SH, Eissa MR, Al-baidhani A, Noordin NK, Sait SM, Al-utaibi KA, Hashim F. 6G Wireless Communications Networks: A Comprehensive Survey. IEEE Access 2021;9:148191-243. [DOI: 10.1109/access.2021.3124812] [Cited by in Crossref: 15] [Cited by in F6Publishing: 5] [Article Influence: 15.0] [Reference Citation Analysis]
15 Lahiri SK, Hulsurkar MM, Wehrens XH. Cellular regeneration as a potential strategy to treat cardiac conduction disorders. J Clin Invest 2021;131:e152185. [PMID: 34596049 DOI: 10.1172/JCI152185] [Reference Citation Analysis]
16 Han F, Wang T, Liu G, Liu H, Xie X, Wei Z, Li J, Jiang C, He Y, Xu F. Materials with Tunable Optical Properties for Wearable Epidermal Sensing in Health Monitoring. Adv Mater 2022;:e2109055. [PMID: 35258117 DOI: 10.1002/adma.202109055] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
17 Francisco-Pascual J, Cantalapiedra-Romero J, Pérez-Rodon J, Benito B, Santos-Ortega A, Maldonado J, Ferreira-Gonzalez I, Rivas-Gándara N. Cardiac monitoring for patients with palpitations. World J Cardiol 2021; 13(11): 608-627 [PMID: 34909127 DOI: 10.4330/wjc.v13.i11.608] [Reference Citation Analysis]
18 Adedinsewo DA, Pollak AW, Phillips SD, Smith TL, Svatikova A, Hayes SN, Mulvagh SL, Norris C, Roger VL, Noseworthy PA, Yao X, Carter RE. Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools. Circ Res 2022;130:673-90. [PMID: 35175849 DOI: 10.1161/CIRCRESAHA.121.319876] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
19 Chen G, Zhao X, Andalib S, Xu J, Zhou Y, Tat T, Lin K, Chen J. Discovering giant magnetoelasticity in soft matter for electronic textiles. Matter 2021;4:3725-40. [DOI: 10.1016/j.matt.2021.09.012] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 7.0] [Reference Citation Analysis]
20 Manlhiot C, van den Eynde J, Kutty S, Ross HJ. A Primer on the Present State and Future Prospects for Machine Learning and Artificial Intelligence Applications in Cardiology. Can J Cardiol 2021:S0828-282X(21)00903-X. [PMID: 34838700 DOI: 10.1016/j.cjca.2021.11.009] [Reference Citation Analysis]
21 Kumar VRS, Choudhary SK, Radhakrishnan PK, Bharath RS, Chandrasekaran N, Sankar V, Sukumaran A, Oommen C. Lopsided Blood-Thinning Drug Increases the Risk of Internal Flow Choking Leading to Shock Wave Generation Causing Asymptomatic Cardiovascular Disease. Glob Chall 2021;5:2000076. [PMID: 33728053 DOI: 10.1002/gch2.202000076] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
22 Cassol C, Sharma S. Nephrology Lagging Behind in Machine Learning Utilization. Kidney Med 2021;3:693-5. [PMID: 34693249 DOI: 10.1016/j.xkme.2021.08.004] [Reference Citation Analysis]
23 Dagher L, Nedunchezhian S, El Hajjar AH, Zhang Y, Deffer O Jr, Russell A, Pottle C, Marrouche N. A Cardiovascular Clinic Patients' Survey to Assess Challenges and Opportunities of Digital Health Adoption During the COVID-19 Pandemic Digital Health Survey During COVID-19. Cardiovasc Digit Health J 2021. [PMID: 34812430 DOI: 10.1016/j.cvdhj.2021.10.007] [Reference Citation Analysis]
24 Sun Z, Zhu M, Lee C. Progress in the Triboelectric Human–Machine Interfaces (HMIs)-Moving from Smart Gloves to AI/Haptic Enabled HMI in the 5G/IoT Era. Nanoenergy Advances 2021;1:81-121. [DOI: 10.3390/nanoenergyadv1010005] [Cited by in Crossref: 16] [Cited by in F6Publishing: 9] [Article Influence: 16.0] [Reference Citation Analysis]
25 Choi YS, Jeong H, Yin RT, Avila R, Pfenniger A, Yoo J, Lee JY, Tzavelis A, Lee YJ, Chen SW, Knight HS, Kim S, Ahn HY, Wickerson G, Vázquez-Guardado A, Higbee-Dempsey E, Russo BA, Napolitano MA, Holleran TJ, Razzak LA, Miniovich AN, Lee G, Geist B, Kim B, Han S, Brennan JA, Aras K, Kwak SS, Kim J, Waters EA, Yang X, Burrell A, San Chun K, Liu C, Wu C, Rwei AY, Spann AN, Banks A, Johnson D, Zhang ZJ, Haney CR, Jin SH, Sahakian AV, Huang Y, Trachiotis GD, Knight BP, Arora RK, Efimov IR, Rogers JA. A transient, closed-loop network of wireless, body-integrated devices for autonomous electrotherapy. Science 2022;376:1006-12. [PMID: 35617386 DOI: 10.1126/science.abm1703] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
26 Krittanawong C, Aydar M, Hassan Virk HU, Kumar A, Kaplin S, Guimaraes L, Wang Z, Halperin JL. Artificial Intelligence-Powered Blockchains for Cardiovascular Medicine. Can J Cardiol 2021:S0828-282X(21)00912-0. [PMID: 34856332 DOI: 10.1016/j.cjca.2021.11.011] [Reference Citation Analysis]
27 Scquizzato T, Semeraro F. No more unwitnessed out-of-hospital cardiac arrests in the future thanks to technology. Resuscitation 2021;170:79-81. [PMID: 34822935 DOI: 10.1016/j.resuscitation.2021.11.010] [Reference Citation Analysis]