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Skip search results from other journals and go to results- 4 JMIR mHealth and uHealth
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Mobile Health Apps for Medical Emergencies: Systematic Review
The following keywords were defined to try to obtain all possible results for this analysis: “emergency” OR “emergencia,” “e Emergency,” “safety” OR “seguridad,” “alert” OR “alerta,” “disaster” OR “desastre,” “SOS,” “112,” and “blood donation” OR “donación de sangre.”
In addition, the language and country used by the different mobile apps were not taken into account. The criterion followed to choose mobile apps in terms of content was to analyze the information offered by each search engine about the app.
JMIR Mhealth Uhealth 2020;8(12):e18513
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Reference 14: Decreto 25/2010, de 17 de junio, sobre precios públicos por actos asistenciales y servicios sanitarios prestados por la Gerencia Regional de Salud(https://www.saludcastillayleon.es/transparencia
JMIR Ment Health 2020;7(11):e15776
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Suicide Prevention Mobile Apps: Descriptive Analysis of Apps from the Most Popular Virtual Stores
On the basis of the experience of mental health professionals from Hospital de Zamora, Castilla y León (Spain), and information and communications technology (ICT) professionals, the following variables were selected to generally describe the publicly available mobile apps in app stores. These variables or parameters were selected per the study’s objective to quantitatively analyze a set of apps aimed at suicide prevention.
JMIR Mhealth Uhealth 2019;7(8):e13885
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Secure Cloud-Based Solutions for Different eHealth Services in Spanish Rural Health Centers
The municipalities chosen are Peñafiel, Cuéllar, Tudela de Duero, and Portillo. The area has 36,000 inhabitants in total, each of which is covered by one doctor and one nurse who provide a physical presence. In addition, these health centers cover small neighboring villages, meaning that there is a variable flow of patients, and therefore numbers cannot be calculated exactly.
J Med Internet Res 2015;17(7):e157
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Mobile Apps in Cardiology: Review
De Vries et al (2013) evaluated the actual use and goals of telemonitoring systems [31], whereas Seto et al (2012) developed a randomized trial of mobile phone-based telemonitoring systems [32] to examine the experience of heart failure patients with these systems [33]. An algorithm for improving the classification of ECGs was developed by Jekova et al (2011), which scores the noise corruption level of ECG data by evaluating several features [34].
JMIR Mhealth Uhealth 2013;1(2):e15
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