The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Jon Arambarri - One of the best experts on this subject based on the ideXlab platform.
-
Health Apps in different mobile platforms: A review in commercial Stores
2016 11th Iberian Conference on Information Systems and Technologies (CISTI), 2016Co-Authors: Isabel Torre Díez, Miguel López-coronado, Beatriz Sainz De Abajo, Joel J. P. C. Rodrigues, Jon ArambarriAbstract:Nowadays, there is a great opportunity for mobile Health using different devices and platforms. A significant number of Health Applications have been already developed for those platforms. According to WHO's latest update (2004) of the Global Burden of Disease, between the most prevalent conditions are iron-deficiency anemia, hearing loss, migraine, low vision, asthma, diabetes mellitus, and others. In this paper, a review of mobile Apps available for different conditions and prevalent diseases will be shown. The search focuses on commercial Applications in platforms such as Google Play by Android, Itunes App Store by Apple, etc. from July to September 2015. A total of 2840 Applications have been found valid in different mobile platforms. Diabetes is the disease with the greatest number of Apps, mainly in Google Play.
-
Security Recommendations for mHealth Apps: Elaboration of a Developer’s Guide
Journal of Medical Systems, 2016Co-Authors: Enrique Pérez Morera, Miguel López-coronado, Begoña García Zapirain, Isabel Torre Díez, Jon ArambarriAbstract:Being the third fastest-growing App category behind games and utilities, mHealth Apps are changing the healthcare model, as medicine today involves the data they compile and analyse, information known as Big Data. However, the majority of Apps are lacking in security when gathering and dealing with the information, which becomes a serious problem. This article presents a guide regarding security solution, intended to be of great use for developers of mHealth Apps. In August 2015 current mobile health Apps were sought out in virtual Stores such as Android Google Play, Apple Itunes App Store etc., in order to classify them in terms of usefulness. After this search, the most widespread weaknesses in the field of security in the development of these mobile Apps were examined, based on sources such as the “OWASP Mobile Security Project, the initiative recently launched by the Office of Civil Rights (OCR), and other articles of scientific interest. An informative, elemental guide has been created for the development of mHealth Apps. It includes information about elements of security and its implementation on different levels for all types of mobile health Apps based on the data that each App manipulates, the associated calculated risk as a result of the likelihood of occurrence and the threat level resulting from its vulnerabilities - high level (Apps for monitoring, diagnosis, treatment and care) from 6 ≤ 9, medium level (calculator, localizer and alarm) from 3 ≤ 6 and low level (informative and educational Apps) from 0 ≤ 3. The guide aims to guarantee and facilitate security measures in the development of mobile health Applications by programmers unconnected to the ITC and professional health areas.
-
Security Recommendations for mHealth Apps: Elaboration of a Developer's Guide
Journal of Medical Systems, 2016Co-Authors: Enrique Pérez Morera, Miguel López-coronado, Begoña García Zapirain, Isabel Torre Díez, Jon ArambarriAbstract:Being the third fastest-growing App category behind games and utilities, mHealth Apps are changing the healthcare model, as medicine today involves the data they compile and analyse, information known as Big Data. However, the majority of Apps are lacking in security when gathering and dealing with the information, which becomes a serious problem. This article presents a guide regarding security solution, intended to be of great use for developers of mHealth Apps. In August 2015 current mobile health Apps were sought out in virtual Stores such as Android Google Play, Apple Itunes App Store etc., in order to classify them in terms of usefulness. After this search, the most widespread weaknesses in the field of security in the development of these mobile Apps were examined, based on sources such as the "OWASP Mobile Security Project, the initiative recently launched by the Office of Civil Rights (OCR), and other articles of scientific interest. An informative, elemental guide has been created for the development of mHealth Apps. It includes information about elements of security and its implementation on different levels for all types of mobile health Apps based on the data that each App manipulates, the associated calculated risk as a result of the likelihood of occurrence and the threat level resulting from its vulnerabilities - high level (Apps for monitoring, diagnosis, treatment and care) from 6?≤?9, medium level (calculator, localizer and alarm) from 3?≤?6 and low level (informative and educational Apps) from 0?≤?3. The guide aims to guarantee and facilitate security measures in the development of mobile health Applications by programmers unconnected to the ITC and professional health areas.
-
Security Recommendations for mHealth Apps: Elaboration of a Developer’s Guide
Journal of Medical Systems, 2016Co-Authors: Enrique Pérez Morera, Miguel López-coronado, Begoña García Zapirain, Isabel Torre Díez, Jon ArambarriAbstract:? 2016, Springer Science+Business Media New York.Being the third fastest-growing App category behind games and utilities, mHealth Apps are changing the healthcare model, as medicine today involves the data they compile and analyse, information known as Big Data. However, the majority of Apps are lacking in security when gathering and dealing with the information, which becomes a serious problem. This article presents a guide regarding security solution, intended to be of great use for developers of mHealth Apps. In August 2015 current mobile health Apps were sought out in virtual Stores such as Android Google Play, Apple Itunes App Store etc., in order to classify them in terms of usefulness. After this search, the most widespread weaknesses in the field of security in the development of these mobile Apps were examined, based on sources such as the ?OWASP Mobile Security Project, the initiative recently launched by the Office of Civil Rights (OCR), and other articles of scientific interest. An informative, elemental guide has been created for the development of mHealth Apps. It includes information about elements of security and its implementation on different levels for all types of mobile health Apps based on the data that each App manipulates, the associated calculated risk as a result of the likelihood of occurrence and the threat level resulting from its vulnerabilities - high level (Apps for monitoring, diagnosis, treatment and care) from 6 ? 9, medium level (calculator, localizer and alarm) from 3 ? 6 and low level (informative and educational Apps) from 0 ? 3. The guide aims to guarantee and facilitate security measures in the development of mobile health Applications by programmers unconnected to the ITC and professional health areas.
Faustina Hwang - One of the best experts on this subject based on the ideXlab platform.
-
popular nutrition related mobile Apps a feature assessment
Jmir mhealth and uhealth, 2016Co-Authors: Rodrigo Zenun Franco, Rosalind Fallaize, Julie Anne Lovegrove, Faustina HwangAbstract:Background: A key challenge in human nutrition is the assessment of usual food intake. This is of particular interest given recent proposals of eHealth personalized interventions. The adoption of mobile phones has created an opportunity for assessing and improving nutrient intake as they can be used for digitalizing dietary assessments and providing feedback. In the last few years, hundreds of nutrition-related mobile Apps have been launched and installed by millions of users. Objective: This study aims to analyze the main features of the most popular nutrition Apps and to compare their strategies and technologies for dietary assessment and user feedback. Methods: Apps were selected from the two largest online Stores of the most popular mobile operating systems—the Google Play Store for Android and the Itunes App Store for iOS—based on popularity as measured by the number of installs and reviews. The keywords used in the search were as follows: calorie(s), diet, diet tracker, dietician, dietitian, eating, fit, fitness, food, food diary, food tracker, health, lose weight, nutrition, nutritionist, weight, weight loss, weight management, weight watcher, and ww calculator. The inclusion criteria were as follows: English language, minimum number of installs (1 million for Google Play Store) or reviews (7500 for Itunes App Store), relation to nutrition (ie, diet monitoring or recommendation), and independence from any device (eg, wearable) or subscription. Results: A total of 13 Apps were classified as popular for inclusion in the analysis. Nine Apps offered prospective recording of food intake using a food diary feature. Food selection was available via text search or barcode scanner technologies. Portion size selection was only textual (ie, without images or icons). All nine of these Apps were also capable of collecting physical activity (PA) information using self-report, the global positioning system (GPS), or wearable integrations. Their outputs focused predominantly on energy balance between dietary intake and PA. None of these nine Apps offered features directly related to diet plans and motivational coaching. In contrast, the remaining four of the 13 Apps focused on these opportunities, but without food diaries. One App—FatSecret—also had an innovative feature for connecting users with health professionals, and another—S Health—provided a nutrient balance score. Conclusions: The high number of installs indicates that there is a clear interest and opportunity for diet monitoring and recommendation using mobile Apps. All the Apps collecting dietary intake used the same nutrition assessment method (ie, food diary record) and technologies for data input (ie, text search and barcode scanner). Emerging technologies, such as image recognition, natural language processing, and artificial intelligence, were not identified. None of the Apps had a decision engine capable of providing personalized diet advice. [JMIR Mhealth Uhealth 2016;4(3):e85]
-
Popular Nutrition-Related Mobile Apps: A Feature Assessment
JMIR mHealth and uHealth, 2016Co-Authors: Rodrigo Zenun Franco, Rosalind Fallaize, Julie Anne Lovegrove, Faustina HwangAbstract:BACKGROUND A key challenge in human nutrition is the assessment of usual food intake. This is of particular interest given recent proposals of eHealth personalized interventions. The adoption of mobile phones has created an opportunity for assessing and improving nutrient intake as they can be used for digitalizing dietary assessments and providing feedback. In the last few years, hundreds of nutrition-related mobile Apps have been launched and installed by millions of users. OBJECTIVE This study aims to analyze the main features of the most popular nutrition Apps and to compare their strategies and technologies for dietary assessment and user feedback. METHODS Apps were selected from the two largest online Stores of the most popular mobile operating systems-the Google Play Store for Android and the Itunes App Store for iOS-based on popularity as measured by the number of installs and reviews. The keywords used in the search were as follows: calorie(s), diet, diet tracker, dietician, dietitian, eating, fit, fitness, food, food diary, food tracker, health, lose weight, nutrition, nutritionist, weight, weight loss, weight management, weight watcher, and ww calculator. The inclusion criteria were as follows: English language, minimum number of installs (1 million for Google Play Store) or reviews (7500 for Itunes App Store), relation to nutrition (ie, diet monitoring or recommendation), and independence from any device (eg, wearable) or subscription. RESULTS A total of 13 Apps were classified as popular for inclusion in the analysis. Nine Apps offered prospective recording of food intake using a food diary feature. Food selection was available via text search or barcode scanner technologies. Portion size selection was only textual (ie, without images or icons). All nine of these Apps were also capable of collecting physical activity (PA) information using self-report, the global positioning system (GPS), or wearable integrations. Their outputs focused predominantly on energy balance between dietary intake and PA. None of these nine Apps offered features directly related to diet plans and motivational coaching. In contrast, the remaining four of the 13 Apps focused on these opportunities, but without food diaries. One App-FatSecret-also had an innovative feature for connecting users with health professionals, and another-S Health-provided a nutrient balance score. CONCLUSIONS The high number of installs indicates that there is a clear interest and opportunity for diet monitoring and recommendation using mobile Apps. All the Apps collecting dietary intake used the same nutrition assessment method (ie, food diary record) and technologies for data input (ie, text search and barcode scanner). Emerging technologies, such as image recognition, natural language processing, and artificial intelligence, were not identified. None of the Apps had a decision engine capable of providing personalized diet advice.
Daryl Johnson - One of the best experts on this subject based on the ideXlab platform.
-
HICSS - Third Party Application Forensics on Apple Mobile Devices
2011 44th Hawaii International Conference on System Sciences, 2011Co-Authors: Alex Levinson, Bill Stackpole, Daryl JohnsonAbstract:Forensics on mobile devices is not new. Law enforcement and academia have been performing forensics on mobile devices for the past several years. Forensics on mobile third party Applications is new. There have been third party Applications on mobile devices before today, but none that provided the number of Applications available in the Itunes App Store. Mobile forensic software tools predominantly addresses "typical" mobile telephony data - contact information, SMS, and voicemail messages. These tools overlook analysis of information saved in third-party Apps. Many third-party Applications installed in Apple mobile devices leave forensically relevant artifacts available for inspection. This includes information about user accounts, timestamps, geolocational references, additional contact information, native files, and various media files. This information can be made readily available to law enforcement through simple and easy-to-use techniques.
-
Third Party Application Forensics on Apple Mobile Devices
2011 44th Hawaii International Conference on System Sciences, 2011Co-Authors: Alex Levinson, Bill Stackpole, Daryl JohnsonAbstract:Forensics on mobile devices is not new. Law enforcement and academia have been performing forensics on mobile devices for the past several years. Forensics on mobile third party Applications is new. There have been third party Applications on mobile devices before today, but none that provided the number of Applications available in the Itunes App Store. Mobile forensic software tools predominantly addresses "typical" mobile telephony data - contact information, SMS, and voicemail messages. These tools overlook analysis of information saved in third-party Apps. Many third-party Applications installed in Apple mobile devices leave forensically relevant artifacts available for inspection. This includes information about user accounts, timestamps, geolocational references, additional contact information, native files, and various media files. This information can be made readily available to law enforcement through simple and easy-to-use techniques.
Jan Vom Brocke - One of the best experts on this subject based on the ideXlab platform.
-
ICIS - Enriching Itunes App Store Categories via Topic Modeling
2020Co-Authors: Svitlana Vakulenko, Oliver Muller, Jan Vom BrockeAbstract:Mobile Application development is an emerging lucrative and fast growing market. With the steady growth of the number of Apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the Apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We Apply Latent Dirichlet Allocation (LDA) to the textual descriptions of Itunes Apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language App descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising Approach, that can help to structure, analyze and manage the content of App repositories. The topics produced complement the original Itunes categories, concretize and extend them by providing insights into the underlying category content.
-
enriching Itunes App Store categories via topic modeling
International Conference on Information Systems, 2014Co-Authors: Svitlana Vakulenko, Oliver Muller, Jan Vom BrockeAbstract:Mobile Application development is an emerging lucrative and fast growing market. With the steady growth of the number of Apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the Apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We Apply Latent Dirichlet Allocation (LDA) to the textual descriptions of Itunes Apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language App descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising Approach, that can help to structure, analyze and manage the content of App repositories. The topics produced complement the original Itunes categories, concretize and extend them by providing insights into the underlying category content.
Svitlana Vakulenko - One of the best experts on this subject based on the ideXlab platform.
-
ICIS - Enriching Itunes App Store Categories via Topic Modeling
2020Co-Authors: Svitlana Vakulenko, Oliver Muller, Jan Vom BrockeAbstract:Mobile Application development is an emerging lucrative and fast growing market. With the steady growth of the number of Apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the Apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We Apply Latent Dirichlet Allocation (LDA) to the textual descriptions of Itunes Apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language App descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising Approach, that can help to structure, analyze and manage the content of App repositories. The topics produced complement the original Itunes categories, concretize and extend them by providing insights into the underlying category content.
-
enriching Itunes App Store categories via topic modeling
International Conference on Information Systems, 2014Co-Authors: Svitlana Vakulenko, Oliver Muller, Jan Vom BrockeAbstract:Mobile Application development is an emerging lucrative and fast growing market. With the steady growth of the number of Apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the Apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We Apply Latent Dirichlet Allocation (LDA) to the textual descriptions of Itunes Apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language App descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising Approach, that can help to structure, analyze and manage the content of App repositories. The topics produced complement the original Itunes categories, concretize and extend them by providing insights into the underlying category content.
-
enriching Itunes App Store categories via topic modeling research in progress
2014Co-Authors: Svitlana Vakulenko, Oliver MullerAbstract:Mobile Application development is an emerging lucrative and fast growing market. With the steady growth of the number of Apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the Apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We Apply Latent Dirichlet Allocation (LDA) to the textual descriptions of Itunes Apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language App descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising Approach, that can help to structure, analyze and manage the content of App repositories. The topics produced complement the original Itunes categories, concretize and extend them by providing insights into the underlying category content.
