BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Majnarić LT, Babič F, O'Sullivan S, Holzinger A. AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity. J Clin Med 2021;10:766. [PMID: 33672914 DOI: 10.3390/jcm10040766] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Aziz F, Cardoso VR, Bravo-Merodio L, Russ D, Pendleton SC, Williams JA, Acharjee A, Gkoutos GV. Multimorbidity prediction using link prediction. Sci Rep 2021;11:16392. [PMID: 34385524 DOI: 10.1038/s41598-021-95802-0] [Reference Citation Analysis]
2 Martínez-garcía M, Hernández-lemus E. Data Integration Challenges for Machine Learning in Precision Medicine. Front Med 2022;8:784455. [DOI: 10.3389/fmed.2021.784455] [Reference Citation Analysis]
3 Zucchelli A, Calderón-Larrañaga A, Vetrano DL. Special Issue-"Multimorbidity Development and Evolution: Clinical Implications". J Clin Med 2021;10:3450. [PMID: 34441746 DOI: 10.3390/jcm10163450] [Reference Citation Analysis]
4 Mattison G, Canfell O, Forrester D, Dobbins C, Smith D, Töyräs J, Sullivan C. The influence of wearables on healthcare outcomes in chronic disease: a systematic review (Preprint). Journal of Medical Internet Research. [DOI: 10.2196/36690] [Reference Citation Analysis]
5 Basto-Abreu A, Barrientos-Gutierrez T, Wade AN, Oliveira de Melo D, Semeão de Souza AS, Nunes BP, Perianayagam A, Tian M, Yan LL, Ghosh A, Miranda JJ. Multimorbidity matters in low and middle-income countries. J Multimorb Comorb 2022;12:26335565221106074. [PMID: 35734547 DOI: 10.1177/26335565221106074] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Brai E, Tonacci A, Brugada-Ramentol V, D'Andrea F, Alberi L. Intercepting Dementia: Awareness and Innovation as Key Tools. Front Aging Neurosci 2021;13:730727. [PMID: 34720991 DOI: 10.3389/fnagi.2021.730727] [Reference Citation Analysis]
7 El Samad M, El Nemar S, Sakka G, El-chaarani H. An innovative big data framework for exploring the impact on decision-making in the European Mediterranean healthcare sector. EMJB 2022. [DOI: 10.1108/emjb-11-2021-0168] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Singh RK, Agrawal S, Sahu A, Kazancoglu Y. Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda. TQM 2021;ahead-of-print. [DOI: 10.1108/tqm-02-2021-0051] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
9 Infante T, Cavaliere C, Punzo B, Grimaldi V, Salvatore M, Napoli C. Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review. Circ Cardiovasc Imaging 2021;14:1133-46. [PMID: 34915726 DOI: 10.1161/CIRCIMAGING.121.013025] [Reference Citation Analysis]
10 Bekić S, Babič F, Pavlišková V, Paralič J, Wittlinger T, Majnarić LT. Clusters of Physical Frailty and Cognitive Impairment and Their Associated Comorbidities in Older Primary Care Patients. Healthcare (Basel) 2021;9:891. [PMID: 34356270 DOI: 10.3390/healthcare9070891] [Reference Citation Analysis]
11 Atalla S, Amin SA, Manoj Kumar MV, Sastry NKB, Mansoor W, Rao A. Autonomous Tool for Monitoring Multi-Morbidity Health Conditions in UAE and India. Front Artif Intell 2022;5:865792. [DOI: 10.3389/frai.2022.865792] [Reference Citation Analysis]
12 Anderson J, Singh J. A Case Study of Using Telehealth in a Rural Healthcare Facility to Expand Services and Protect the Health and Safety of Patients and Staff. Healthcare (Basel) 2021;9:736. [PMID: 34203888 DOI: 10.3390/healthcare9060736] [Reference Citation Analysis]
13 Bosnic Z, Yildirim P, Babič F, Šahinović I, Wittlinger T, Martinović I, Majnaric LT. Clustering Inflammatory Markers with Sociodemographic and Clinical Characteristics of Patients with Diabetes Type 2 Can Support Family Physicians' Clinical Reasoning by Reducing Patients' Complexity. Healthcare (Basel) 2021;9:1687. [PMID: 34946413 DOI: 10.3390/healthcare9121687] [Reference Citation Analysis]