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A Systematic Review of Healthcare Applications for Smartphones
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Background: Advanced mobile communications and portable computation are now combined in handheld devices called “smartphones”, which are also capable of running third-party software. The number of smartphone users is growing rapidly, including among healthcare professionals. The purpose of this study was to classify smartphone-based healthcare technologies as discussed in academic literature according to their functionalities, and summarize articles in each category. Methods: In April 2011, MEDLINE was searched to identify articles that discussed the design, development, evaluation, or use of smartphone-based software for healthcare professionals, medical or nursing students, or patients. A total of 55 articles discussing 83 applications were selected for this study from 2,894 articles initially obtained from the MEDLINE searches. Results: A total of 83 applications were documented: 57 applications for healthcare professionals focusing on disease diagnosis (21), drug reference (6), medical calculators (8), literature search (6), clinical communication (3), Hospital Information System (HIS) client applications (4), medical training (2) and general healthcare applications (7); 11 applications for medical or nursing students focusing on medical education; and 15 applications for patients focusing on disease management with chronic illness (6), ENT-related (4), fall-related (3), and two other conditions (2). The disease diagnosis, drug reference, and medical calculator applications were reported as most useful by healthcare professionals and medical or nursing students. Conclusions: Many medical applications for smartphones have been developed and widely used by health professionals and patients. The use of smartphones is getting more attention in healthcare day by day. Medical applications make smartphones useful tools in the practice of evidence-based medicine at the point of care, in addition to their use in mobile clinical communication. Also, smartphones can play a very important role in patient education, disease self-management, and remote monitoring of patients.
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![Figure 3 Smartphone U.S. Market Share Feb-2010 to May-2011[3-5]. This figure presents the market share of five major smartphone platforms (i.e. Palm Web OS, Windows Phone, BlackBerry, iOS, Android) in the United States during the period of 2010 – 2011. In the middle of 2011, Android has become the leader in smartphone market share while all other platforms have shown decreasing trend except iOS. The market share of iOS was almost consistent during this period.](/paper-figures/876942c884d24b05a911471358665106/a-systematic-review-of-healthcare-applications-for-smartphones-figure-3.jpg)
![Figure 4 Smartphone Worldwide Market Share Forecast 2015[133]. This histogram presents the worldwide market share forecast data from IDC for six smartphone OS platforms in 2015. Android is predicted to be the global market leader in smartphones acquiring almost half of the market share by 2015.](/paper-figures/22114fd036e94f0eaa87d386e5ea6a2c/a-systematic-review-of-healthcare-applications-for-smartphones-figure-4.jpg)
![Figure 5 Smartphone Worldwide Market Share Forecast 2010–2015[134]. This figure presents the market share forecast data from Gartner for five smartphone OS platforms up to 2015. Android is predicted to be the leader in smartphone market by 2015 acquiring almost half of the market share. Symbian OS will lose almost all of the market share since its vendor Nokia announced in February, 2011 to shift from Symbian OS to Windows Phone 7 [153], thus global market share for Windows Phone is forecast to gain by 2015, placing the platform in second position.](/paper-figures/09c0d68d483a4f9898878613568d2a33/a-systematic-review-of-healthcare-applications-for-smartphones-figure-5.jpg)
![Figure 6 Number of Applications in Apple’s App Store and Google’s Android Market (July’08 – Nov’11)[141-156]. This figure presents the growth rate of two major smartphone application stores: Apples’s App Store and Google’s Android Market, during the period of July, 2008 to November 2011. Both of the stores are growing very fast. According to the most recent updates, the total number of applications in Apple’s App Store is more than 425,000 as of July, 2011 [141] and in Android Market is more than 352,800 as of November, 2011 [152]. Overall, the Apple’s App Store is currently leading in terms of the application store size; however, the growth rate is much slower than Android Market.](/paper-figures/2f444a7cb69747a7b85719d9048b89a9/a-systematic-review-of-healthcare-applications-for-smartphones-figure-6.jpg)
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“Generally, health care apps have been exhaustively discussed and reviewed in the literature [58]; however, the number of papers that focus on reviewing and evaluating tinnitus-related smartphone apps is underwhelming.”
From Smartphone and mobile health apps for tinnitus: Systematic identification, analysis, and assessment (2020) · cites this paper as [58]
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Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Studies in Health Technology and Informatics
Aphinyanaphongs, Y., & Aliferis, C. (2007) · Cited by 1,247
Text messaging as a tool for behavior change in disease prevention and management
Cole-Lewis, H., & Kershaw, T. (2010) · Epidemiologic Reviews · doi:10.1093/epirev/mxq004 · Cited by 1,190
Boulos, M. N. K., Wheeler, S., Tavares, C., & Jones, R. B. (2011) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-10-24 · Cited by 1,123
Healthcare via Cell Phones: A Systematic Review
Krishna, S., Boren, S. A., & Balas, E. A. (2009) · Telemedicine and e-Health · doi:10.1089/tmj.2008.0099 · Cited by 882
Adolphe Quetelet (1796 1874) the average man and indices of obesity
Eknoyan, G. (2007) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfm517 · Cited by 746
Recent advances: Consumer health informatics
Eysenbach, G. (2000) · BMJ · doi:10.1136/bmj.320.7251.1713 · Cited by 670
Liang, X., Wang, Q., Yang, X., Cao, J., Chen, J., Mo, X., Huang, J., Wang, L., & Gu, D. (2011) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03180.x · Cited by 515
Wireless World: Social and Interactional Aspects of the Mobile Age
Brown, B. A. T., & Green, N. H. (2001) · Cited by 367
Research works printed but not linked: 10
- US Mobile Year in Review. [http://www2.comscore.com/l/1552/ileYearinReview2010Webinar-pdf/QOZR3]
- Knowledge on call: Physicians increasingly are discovering smartphones serve a purpose beyond being a convenient communication gadget. [http://www.ama-assn.org/amednews/2009/01/05/plus/bisa0105.pdf]
- M B: Proceedings of Ume°a’s 14th Student Conference in Computing Science. Opportunities and Challenges when Applying Mobile Technology in Health Care. 2010, UME°A, SWEDEN: UME°A UNIVERSITY, 1-12.
- Sarasohn-Kahn J: How Smartphones Are Changing Health Care for Consumers and Providers. 2010, Oakland, CA: California HealthCare Foundation,http://posterous.com/getfile/files.posterous.com/mobihealth/Pqvz1Ff7GcGuEwfNYj1WFMiuBfqUe0h2NY7fqAisAPu0okpu0fmuCGAytEI0/HowSmartPhonesChngHealthcare.pdf,
- Zhang T, Wang J, Liu P, Hou J: Fall detection by embedding an accelerometer in cellphone and using KFD algorithm. International Journal of Computer Science and Network Security: IJCSNS. 2006, 6: 277-284.
- de Buenaga M, Gachet D, Maña MJ, de la Villa M, Mata J: SIGIR 2008 Workshop on Mobile Information Retrieval. Clustering and Summarizing Medical Documents to Improve Mobile Retrieval. 2008, Singapore, 54-57.
- Mayo Clinic Proceedings. Tri JL, Severson RP, Hyberger LK, Hayes DL. 2007, Mayo Clinic, 282-285. 82nd · DOI
- Bertman J: Tech 101: a new generation of smartphones. MDNG Neurology. 2009, 11: 26-
- Hoyt RE, Cruz RW: Chapter 11: Mobile Technology. In Medical Informatics. Practical Guide for Healthcare and Information Technology Professionals. Edited by: Hoyt RE. 2010, Lulu Enterprises Inc, 199-217. 4th
- Introducing the T-Mobile G2 with Google — the First Smartphone Delivering 4G Speeds on T-Mobile’s Super-Fast HSPA+ Network. [http://www.htc.com/us/press/introducing-the-t-mobile-g2-with-google--the-first-smartphone-delivering-4g-speeds-on-t-mobiles-super-fast-hspa-network/19]
Cited by
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Finkbiner, M. J., Gaina, K. M., McRandall, M. C., Wolf, M. M., Pardo, V., Reid, K., Adams, B., & Galen, S. S. (2017) · Journal of Visualized Experiments · doi:10.3791/54659 · Cited by 29
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Washington, P. Y., Kalantarian, H., Tariq, Q., Schwartz, J. N., Dunlap, K., Chrisman, B., Varma, M., Ning, M., Kline, A., Stockham, N., et al. (2019) · Journal of Medical Internet Research · doi:10.2196/13668 · Cited by 29
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Bibault, J., Leroy, T., Blanchard, P., Biau, J., Cervellera, M., Diaz, O., Faivre, J.-C., Fumagalli, I., Lescut, N., Martin, V., et al. (2014) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2014.05.012 · Cited by 28
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Lim, H. M., Dunn, A. G., Ooi, S. M. F., Teo, C. H., Abdullah, A. B., Woo, W. J., & Ng, C. J. (2020) · Family Practice · doi:10.1093/fampra/cmaa103 · Cited by 27
Zhang, L., & Jiang, S. (2021) · Health Education Research · doi:10.1093/her/cyab005 · Cited by 27
Gutiérrez‐Puertas, V., Gutiérrez‐Puertas, L., Aguilera‐Manrique, G., Rodríguez-García, M. C., & Márquez‐Hernández, V. V. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18031307 · Cited by 27
Dunham, M., Bonacaro, A., Schofield, P., Bacon, L., Spyridonis, F., & Mehrpouya, H. (2021) · Geriatrics · doi:10.3390/geriatrics6020040 · Cited by 28
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Baum, R., Epstein, J. N., & Kelleher, K. J. (2013) · Current Psychiatry Reports · doi:10.1007/s11920-013-0369-0 · Cited by 27
Bedell, G. M., Wade, S. L., Turkstra, L. S., Haarbauer-Krupa, J. K., & King, J. A. (2016) · Developmental Neurorehabilitation · doi:10.1080/17518423.2016.1237584 · Cited by 27
Data Collection Mechanisms in Health and Wellness Apps: Review and Analysis
Philip, B. J., Abdelrazek, M., Bonti, A., Barnett, S., & Grundy, J. (2021) · JMIR mhealth and uhealth · doi:10.2196/30468 · Cited by 28
Mobile remote-presence devices for point-of-care health care delivery
Mendez, I. M., & den Hof, M. C. V. (2013) · Canadian Medical Association Journal · doi:10.1503/cmaj.120223 · Cited by 26
Método de valoración de aplicaciones móviles de salud en español: el índice iSYScore
Grau, I., Kostov, B., Gallego, J. A., Grajales, F. J., III, Fernández-Luque, L., & Sisó‐Almirall, A. (2016) · Medicina de Familia SEMERGEN · doi:10.1016/j.semerg.2015.12.001 · Cited by 26
Whitaker, A. T., Gesheff, M. G., Jauregui, J. J., & Herzenberg, J. E. (2016) · Journal of Children s Orthopaedics · doi:10.1007/s11832-016-0761-5 · Cited by 26
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Tobón, D. P., & Falk, T. H. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2638120 · Cited by 27
Oliveira, É., Crosewski, N. I., Silva, A. L. M., Ribeiro, C. T., de Oliveira, C. M., Fogaça, R. T. H., & Dias, F. A. L. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1438-7 · Cited by 25
Chika, E. U., Precious, B. D. U., King-David, B. A., Ezenri, G., Okechukwu, B. N. T., Chidozie, C., & Madubugwu, R. C. (2024) · Telehealth and Medicine Today · doi:10.30953/thmt.v9.445 · Cited by 28
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Thinnukool, O., Khuwuthyakorn, P., & Wientong, P. (2017) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v11i3.6757 · Cited by 25
Vandersman, P., Newton-John, T. R. O., & Phillips, J. L. (2020) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2020.104062 · Cited by 27
Peng, S., Wang, A., Lian, Y., Zhang, X., Zeng, B., Chen, Q., Yang, H., Li, J., Li, L., Dan, J., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0258508 · Cited by 25
Dailah, H. G. (2022) · Journal of Healthcare Engineering · doi:10.1155/2022/4383303 · Cited by 25
Sandholzer, M., Rurik, I., Deutsch, T., & Frese, T. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0125-y · Cited by 25
Meyer, A. J., Stomski, N. J., Innes, S. I., & Armson, A. J. (2015) · Anatomical Sciences Education · doi:10.1002/ase.1555 · Cited by 25
Els, F., & Cilliers, L. (2017) · Conference on Information Communications Technology and Society (ICTAS) · doi:10.1109/ictas.2017.7920658 · Cited by 25
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Seah, H. M., Burney, M., Phan, M., Shell, D., Wu, J., Zhou, K. Z., Brooks, O., Coulton, B., Maingard, J. T., Tang, J. Y. ‐., et al. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00725 · Cited by 25
Quamar, A. H., Schmeler, M. R., Collins, D. M., & Schein, R. M. (2019) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2019.1650298 · Cited by 25
Aida, A., Svensson, T., Svensson, A. K., Chung, U., & Yamauchi, T. (2020) · JMIR mhealth and uhealth · doi:10.2196/18316 · Cited by 25
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Barutçu, S. (2019) · International Journal of Health Care Quality Assurance · doi:10.1108/ijhcqa-08-2018-0195 · Cited by 24
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Debnath, S. (2023) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2023.19.1.1335 · Cited by 25
McHenry, M. S., Fischer, L. J., Chun, Y., & Vreeman, R. (2017) · Global Health Promotion · doi:10.1177/1757975917715035 · Cited by 24
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Badawy, R., Raykov, Y. P., Evers, L. J. W., Bloem, B. R., Faber, M. J., Zhan, A., Claes, K., & Little, M. A. (2018) · Sensors · doi:10.3390/s18041215 · Cited by 24
Clebone, A., Strupp, K. M., Whitney, G., Anderson, M. R., Hottle, J., Fehr, J. J., Yaster, M., Schleelein, L. E., & Burian, B. K. (2018) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000003935 · Cited by 24
van Velsen, L., Beaujean, D. J., Wentzel, J., Van Steenbergen, J. E., & van Gemert-Pijnen, J. E. (2015) · Health Informatics Journal · doi:10.1177/1460458213496419 · Cited by 23
Hombaiah, C., Madhu, B., Gopi, A., & Narayana Murthy, M. R. (2022) · PLOS ONE · doi:10.1371/journal.pone.0273070 · Cited by 23
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Ribeiro, N., Moreira, L., Almeida, A. M. P., & Santos‐Silva, F. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.10.013 · Cited by 23
Signorelli, G. R., Monteiro-Guerra, F., Rivera-Romero, O., Núñez-Benjumea, F. J., & Fernández-Luque, L. (2022) · JMIR Formative Research · doi:10.2196/32354 · Cited by 24
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Erickson, K. (2015) · The Open Journal of Occupational Therapy · doi:10.15453/2168-6408.1132 · Cited by 23
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Andrawis, J. P., Muzykewicz, D. A., & Franko, O. I. (2016) · Orthopedics · doi:10.3928/01477447-20151228-01 · Cited by 23
Aungst, T. D., & Belliveau, P. (2015) · Journal of Interprofessional Care · doi:10.3109/13561820.2015.1049339 · Cited by 23
Using tablets in medical consultations: Single loop and double loop learning processes
Reychav, I., Kumi, R., Sabherwal, R., & Azuri, J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.03.020 · Cited by 23
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Zhang, C., Zhang, X., & Halstead-Nussloch, R. (2014) · Issues in Information Systems · doi:10.48009/2_iis_2014_59-66 · Cited by 23
Apps for Management of Sick Newborn: Evaluation of Impact on Health Care Professionals
Thukral, A., Joshi, M., Joshi, P., Prakash, V., Adkoli, B. V., & Deorari, A. K. (2014) · Journal of Tropical Pediatrics · doi:10.1093/tropej/fmu032 · Cited by 23
Chen, D. Z., & Tan, C. (2016) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.v45n1p6 · Cited by 23
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Teo, C. H., Ng, C. J., & White, A. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169435 · Cited by 23
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Holmes, W. S., Moorhead, S. A., COATES, V. E., Bond, R., & Zheng, H. (2018) · European Journal of Public Health · doi:10.1093/eurpub/cky171 · Cited by 23
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Inupakutika, D., Kaghyan, S., Akopian, D., Chalela, P., & Ramírez, A. G. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103420 · Cited by 23
Wang, S. C., Au, Y., Ramírez-GarcíaLuna, J. L., Lee, L., & Berry, G. K. (2020) · Advances in Skin & Wound Care · doi:10.1097/01.asw.0000694136.29135.02 · Cited by 23
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Hubiche, T., Valério, L., Boralevi, F., Mahe, E., Bodemer Skandalis, C., Phan, A., del Giudice, P., & for the Research Group of the French Society of Pediatric Dermatology (Groupe de Recherche de la Société Française de Dermatologie Pédiatrique) (2016) · JAMA Dermatology · doi:10.1001/jamadermatol.2015.2977 · Cited by 22
Cherrez-Ojeda, I., Vanegas, E., Cherrez, A., Felix, M., Weller, K., Magerl, M., Maurer, R. R., Mata, V. L., Kasperska-Zajac, A., Sikora, A., et al. (2021) · World Allergy Organization Journal · doi:10.1016/j.waojou.2021.100542 · Cited by 22
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Pavlas, J., Krejcar, O., Marešová, P., & Selamat, A. (2018) · Computers · doi:10.3390/computers8010001 · Cited by 22
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Ruyobeza, B., Grobbelaar, S. S. S., & Botha, A. (2022) · Systematic Reviews · doi:10.1186/s13643-022-02033-z · Cited by 24
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Austin, N. S., Goldhaber-Fiebert, S. N., Daniels, K. I., Arafeh, J. M. R., Grenon, V., Welle, D., & Lipman, S. S. (2016) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000001601 · Cited by 22
Nilsson, P. M., Todsen, T., Subhi, Y., Graumann, O., Nolsøe, C., & Tolsgaard, M. G. (2017) · Ultraschall in der Medizin - European Journal of Ultrasound · doi:10.1055/s-0043-119354 · Cited by 22
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Zhang, C., Fan, L., Chai, Z., Yu, C., & Song, J. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01238-3 · Cited by 22
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Green, M. S., Mathew, J. J., Venkatesh, A. G., Green, P., & Tariq, R. (2018) · Anesthesiology Research and Practice · doi:10.1155/2018/8694357 · Cited by 22
Hyun, C. S., McMenamin, J. P., Ko, O., & Kim, S. (2020) · JMIR mhealth and uhealth · doi:10.2196/15098 · Cited by 22
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Cong, J., Gao, M., Wang, Y., Chen, R., & Wang, P. (2020) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1900242 · Cited by 21
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Craven, M. P., Lang, A. R., & Martin, J. L. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-07635-5_2 · Cited by 21
Kim, H.-Y., Park, H., Min, Y. H., & Jeon, E. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2512 · Cited by 21
Young‐Afat, D. A., van Gils, C. H., Bruinvels, D. J., van der Pol, C. C., Witkamp, A. J., Sijtsema, S., Jonasse, Y., Bijlsma, R. M., Ausems, M. G. E. M., Bos, A. M. E., et al. (2016) · JMIR Cancer · doi:10.2196/cancer.5334 · Cited by 21
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Martínez, F. T., Tobar, C., & Taramasco, C. (2017) · BMC Medical Education · doi:10.1186/s12909-017-1010-4 · Cited by 21
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Marin-Gomez, F. X., Vidal‐Alaball, J., Poch, P. R., Sariola, C. J., Taberner, R., & Mendioroz, J. (2020) · Journal of Primary Care & Community Health · doi:10.1177/2150132720937831 · Cited by 21
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Kim, D., & Joshi, K. P. (2021) · IEEE International Conference on Big Data Security on Cloud, IEEE International Conference on High Performance and Smart Computing, and IEEE International Conference on Intelligent Data and Security (BigDataSecurity/HPSC/IDS) · doi:10.1109/bigdatasecurityhpscids52275.2021.00013 · Cited by 21
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Ngo, T. T., Ahad, M. A. R., Antar, A. D., Ahmed, M., Muramatsu, D., Makihara, Y., Yagi, Y., Inoue, S., Hossain, T., & Hattori, Y. (2019) · International Conference on Biometrics · doi:10.1109/icb45273.2019.8987235 · Cited by 20
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Bauer, D. C., Gaff, C., Dinger, M. E., Caramins, M. C., Buske, F. A., Fenech, M. F., Hansen, D. T., & Cobiac, L. (2014) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2014.04.001 · Cited by 20
Rughiniş, C., Rughinis, R. V., & Matei, Ș. (2015) · Ethics and Information Technology · doi:10.1007/s10676-016-9385-1 · Cited by 20
Vashist, S. K., & Luong, J. H. T. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811762-0.00017-7 · Cited by 20
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Pereira, I. M., Bonfim, D., Peres, H. H. C., Góes, R. F., & Gaidzinski, R. R. (2017) · Acta Paulista de Enfermagem · doi:10.1590/1982-0194201700069 · Cited by 20
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Deshpande, S. S., Radke, U. M., Karemore, T. V., Mohril, R., Rawlani, S., & Ingole, P. D. (2019) · The Journal of Contemporary Dental Practice · doi:10.5005/jp-journals-10024-2496 · Cited by 19
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Metadata
- Authors
- Mosa, A. S. M., Yoo, I., & Sheets, L.
- Affiliations
- University of Missouri (US)
- Corresponding author
- Yoo, Illhoi
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2012-07-10
- Volume
- 12
- Issue
- 1
- Pages
- 67-67
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC3534499
- OpenAlex
- W2168217134
- Cited by
- 1,184
- References
- 122
- Citations by year
- 2026: 23 · 2025: 55 · 2024: 69 · 2023: 75 · 2022: 88 · 2021: 102 · 2020: 108 · 2019: 92 · 2018: 110 · 2017: 132 · 2016: 122 · 2015: 95 · 2014: 69 · 2013: 41 · 2012: 3
- FWCI
- 10.12
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Food and Drug Administration
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Physical Sciences › Computer Science › Information Systems › Mobile and Web Applications
- Keywords
- mobile application, mobile health, healthcare workers, medical students, nursing students, disease diagnosis, drug reference, medical calculators, clinical communication, hospital information systems, medical education, patient self-management, chronic disease, patient education, remote patient monitoring, evidence-based medicine
- MeSH terms
- Medical Informatics Applications, Cell Phone
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