Machine Learning in Medical Emergencies: a Systematic Review and Analysis.

Despite the increasing demand for artificial intelligence research in medicine, the functionalities of his methods in health emergency remain unclear. Therefore, the authors have conducted this systematic review and a global overview study which aims to identify, analyse, and evaluate the research available on different platforms, and its implementations in healthcare emergencies. The methodology applied for the identification and selection of the scientific studies and the different applications consist of two methods. On the one hand, the PRISMA methodology was carried out in Google Scholar, IEEE Xplore, PubMed ScienceDirect, and Scopus. On the other hand, a review of commercial applications found in the best-known commercial platforms (Android and iOS). A total of 20 studies were included in this review. Most of the included studies were of clinical decisions (n = 4, 20%) or medical services or emergency services (n = 4, 20%). Only 2 were focused on m-health (n = 2, 10%). On the other hand, 12 apps were chosen for full testing on different devices. These apps dealt with pre-hospital medical care (n = 3, 25%) or clinical decision support (n = 3, 25%). In total, half of these apps are based on machine learning based on natural language processing. Machine learning is increasingly applicable to healthcare and offers solutions to improve the efficiency and quality of healthcare. With the emergence of mobile health devices and applications that can use data and assess a patient's real-time health, machine learning is a growing trend in the healthcare industry.

Predicting Absenteeism and Temporary Disability Using Machine Learning: a Systematic Review and Analysis.

The main objective of this paper is to present a systematic analysis and review of the state of the art regarding the prediction of absenteeism and temporary incapacity using machine learning techniques. Moreover, the main contribution of this research is to reveal the most successful prediction models available in the literature. A systematic review of research papers published from 2010 to the present, related to the prediction of temporary disability and absenteeism in available in different research databases, is presented in this paper. The review focuses primarily on scientific databases such as Google Scholar, Science Direct, IEEE Xplore, Web of Science, and ResearchGate. A total of 58 articles were obtained from which, after removing duplicates and applying the search criteria, 18 have been included in the review. In total, 44% of the articles were published in 2019, representing a significant growth in scientific work regarding these indicators. This study also evidenced the interest of several countries. In addition, 56% of the articles were found to base their study on regression methods, 33% in classification, and 11% in grouping. After this systematic review, the efficiency and usefulness of artificial neural networks in predicting absenteeism and temporary incapacity are demonstrated. The studies regarding absenteeism and temporary disability at work are mainly conducted in Brazil and India, which are responsible for 44% of the analyzed papers followed by Saudi Arabia, and Australia which represented 22%. ANNs are the most used method in both classification and regression models representing 83% and 80% of the analyzed works, respectively. Only 10% of the literature use SVM, which is the less used method in regression models. Moreover, Naïve Bayes is the less used method in classification models representing 17%.

Proposing New Blockchain Challenges in eHealth.

The blockchain technology has reached a great boom in the health sector, due to its importance to overcome interoperability and security challenges of the EHR and EMR systems in eHealth. The main objective of this work is to show a review of the existing research works in the literature, referring to the new blockchain technology applied in ehealth and exposing the possible research lines and trends in which this technology can be focused. The search for blockchain studies in eHealth field was carried out in the following databases: IEEE Xplore, Google Scholar, Science Direct, PubMed, Web of Science and ResearchGate from 2010 to the present. Different search criteria were established such as: "Blockchain" AND ("eHealth" OR "EHR" OR "electronic health records" OR "medicine") selecting the papers considered of most interest. A total of 84 publications on blockchain in eHealth were found, of which 18 have been identified as relevant works, 5.56% correspond to the year 2016, 22.22% to 2017 and 72.22% to 2018. Many of the publications found show how this technology is being developed and applied in the health sector and the benefits it provides. The new blockchain technology applied in eHealth identifies new ways to share the distributed view of health data and promotes the advancement of precision medicine, improving health and preventing diseases.

Social Robots for People with Aging and Dementia: A Systematic Review of Literature.

Background: Social robots are currently a form of assistive technology for the elderly, healthy, or with cognitive impairment, helping to maintain their independence and improve their well-being. Objective: The main aim of this article is to present a review of the existing research in the literature, referring to the use of social robots for people with dementia and/or aging. Methods: Academic databases that were used to perform the searches are IEEE Xplore, PubMed, Science Direct, and Google Scholar, taking into account as date of publication the last 10 years, from 2007 to the present. Several search criteria were established such as "robot" AND "dementia," "robot" AND "cognitive impairment," "robot" AND "social" AND "aging," and so on., selecting the articles of greatest interest regarding the use of social robots in elderly people with or without dementia. Results: This search found a total of 96 articles on social robots in healthy people and with dementia, of which 38 have been identified as relevant work. Many of the articles show the acceptance of older people toward social robots. Conclusion: From the review of the research articles analyzed, it can be said that use of social robots in elderly people without cognitive impairment and with dementia, help in a positive way to work independently in basic activities and mobility, provide security, and reduce stress.

Systematic Review about QoS and QoE in Telemedicine and eHealth Services and Applications.

The provision of Quality of Service (QoS) and Quality of Experience (QoE) is a mandatory requirement when transmitting telemedicine traffic, due to information relevance to maintain the patient's health. The main objective of this paper is to present a review of existing research works in the literature, referring to QoS and QoE in telemedicine and eHealth applications. The academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct and Web of Science, taking into account the date of publication from 2008 to the present. These databases cover the most information of scientific texts in multidisciplinary fields, engineering and medicine. Several search criteria were established such as 'QoS' AND 'eHealth' OR 'Telemedicine', 'QoE' AND 'eHealth' AND 'Telemedicine' etc. selecting the items of greatest interest. A total of 248 papers related to QoS and QoE in telemedicine and eHealth have been found, of which 39 papers have been identified as relevant works. The results show that the percentage of studies related to QoS in literature is higher with 74.36% to QoE with 25.64%. From the review of the research articles analyzed, it can be said that QoS and QoE in telemedicine and eHealth are important and necessary factors to guarantee the privacy, reliability, quality and security of data in health care systems.

Data Mining Algorithms and Techniques in Mental Health: A Systematic Review.

Data Mining in medicine is an emerging field of great importance to provide a prognosis and deeper understanding of disease classification, specifically in Mental Health areas. The main objective of this paper is to present a review of the existing research works in the literature, referring to the techniques and algorithms of Data Mining in Mental Health, specifically in the most prevalent diseases such as: Dementia, Alzheimer, Schizophrenia and Depression. Academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct, Scopus and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present. Several search criteria were established such as 'techniques' AND 'Data Mining' AND 'Mental Health', 'algorithms' AND 'Data Mining' AND 'dementia' AND 'schizophrenia' AND 'depression', etc. selecting the papers of greatest interest. A total of 211 articles were found related to techniques and algorithms of Data Mining applied to the main Mental Health diseases. 72 articles have been identified as relevant works of which 32% are Alzheimer's, 22% dementia, 24% depression, 14% schizophrenia and 8% bipolar disorders. Many of the papers show the prediction of risk factors in these diseases. From the review of the research articles analyzed, it can be said that use of Data Mining techniques applied to diseases such as dementia, schizophrenia, depression, etc. can be of great help to the clinical decision, diagnosis prediction and improve the patient's quality of life.

Managing and Controlling Stress Using mHealth: Systematic Search in App Stores.

BACKGROUND: Traditional stress management techniques have been proven insufficient to tackle the needs of today's population. Computational-based techniques and now mobile health (mHealth) apps are showing promise to enable ease of use and access while educating end users on self-management. OBJECTIVE: The main aim of this paper was to put forward a systematic review of mHealth apps for stress management. METHODS: The scenario chosen for this study consists of a sample of the most relevant mHealth apps found on the British and Spanish online stores of the two main mobile operating systems: iOS and Android. The apps have been categorized and scored base on their impact, presence, number of results, language, and operating system. RESULTS: A total of 433 different mobile apps for stress management was analyzed. Of these apps, 21.7% (94/433) belonged to the "relaxing music" category, 10.9% (47/433) were in the "draw and paint" category, 1.2% (5/433) belonged to the "heart rate control" category, and 1.2% (5/433) fell under "integral methodology." Only 2.0% (8/433) of the apps qualified as high or medium interest while 98.0% were low interest. Furthermore, 2.0% (8/433) of the apps were available on both iOS and Android, and 98% of apps ran on only one platform (iOS or Android). CONCLUSIONS: There are many low-value apps available at the moment, but the analysis shows that they are adding new functionalities and becoming fully integrated self-management systems with extra capabilities such as professional assistance services and online support communities.

Mobile Apps for Suicide Prevention: Review of Virtual Stores and Literature.

BACKGROUND: The best manner to prevent suicide is to recognize suicidal signs and signals, and know how to respond to them. OBJECTIVE: We aim to study the existing mobile apps for suicide prevention in the literature and the most commonly used virtual stores. METHODS: Two reviews were carried out. The first was done by searching the most commonly used commercial app stores, which are iTunes and Google Play. The second was a review of mobile health (mHealth) apps in published articles within the last 10 years in the following 7 scientific databases: Science Direct, Medline, PsycINFO, Embase, The Cochrane Library, IEEE Xplore, and Google Scholar. RESULTS: A total of 124 apps related to suicide were found in the cited virtual stores but only 20 apps were specifically designed for suicide prevention. All apps were free and most were designed for Android. Furthermore, 6 relevant papers were found in the indicated scientific databases; in these studies, some real experiences with physicians, caregivers, and families were described. The importance of these people in suicide prevention was indicated. CONCLUSIONS: The number of apps regarding suicide prevention is small, and there was little information available from literature searches, indicating that technology-based suicide prevention remains understudied. Many of the apps provided no interactive features. It is important to verify the accuracy of the results of different apps that are available on iOS and Android. The confidence generated by these apps can benefit end users, either by improving their health monitoring or simply to verify their body condition.

A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector.

The main objective of this paper is to present a review of existing researches in the literature, referring to Big Data sources and techniques in health sector and to identify which of these techniques are the most used in the prediction of chronic diseases. Academic databases and systems such as IEEE Xplore, Scopus, PubMed and Science Direct were searched, considering the date of publication from 2006 until the present time. Several search criteria were established as 'techniques' OR 'sources' AND 'Big Data' AND 'medicine' OR 'health', 'techniques' AND 'Big Data' AND 'chronic diseases', etc. Selecting the paper considered of interest regarding the description of the techniques and sources of Big Data in healthcare. It found a total of 110 articles on techniques and sources of Big Data on health from which only 32 have been identified as relevant work. Many of the articles show the platforms of Big Data, sources, databases used and identify the techniques most used in the prediction of chronic diseases. From the review of the analyzed research articles, it can be noticed that the sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality.

Dual System for Enhancing Cognitive Abilities of Children with ADHD Using Leap Motion and eye-Tracking Technologies.

Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder marked by an ongoing pattern of inattention and/or hyperactivity-impulsivity that affects with development or functioning. It affects 3-5% of all American and European children. The objective of this paper is to develop and test a dual system for the rehabilitation of cognitive functions in children with ADHD. A technological platform has been developed using the ". NET framework", which makes use of two physiological sensors, -an eye-tracker and a hand gesture recognition sensor- in order to provide children with the opportunity to develop their learning and attention skills. The two physiological sensors we utilized for the development are the Tobii X1 Light Eye Tracker and the Leap Motion. SUS and QUIS questionnaires have been carried out. 19 users tested the system and the average age was 10.88 years (SD = 3.14). The results obtained after tests were performed were quite positive and hopeful. The learning of the users caused by the system and the interfaces item got a high punctuation with a mean of 7.34 (SD = 1.06) for SUS questionnaire and 7.73 (SD = 0.6) for QUIS questionnaire. We didn't find differences between boys and girls. The developed multimodal rehabilitation system can help to children with attention deficit and learning issues. Moreover, the teachers may utilize this system to track the progression of their students and see their behavior.

Information and Communications Technologies Health Projects in Panama: A Systematic Review and their Relation with Public Policies.

This paper presents a review about Information and Communications Technologies (ICTs) health projects in Panama. The main contribution is to provide a vision of the situation in Panama, allowing an understanding of the dynamics of health policies and how they have affected the implementation of ICT's Projects to improve the health of Panamanians. We analyze the projects found with ICT's in health of Panama, which allow us to see a perspective of projects information is obtained from 2000 to 2016, however it is important to highlight that there may be other projects that we do not know because we did not find enough information or evidence of the same. That is why this review has interviews with key personnel, who have guided us with the search for information. 56% of technology projects are concentrated in the capital city and only 16% in the province of Chiriquí. 64% of these projects are focused on the development of information systems, mainly focused on electronic patient registration. And 60% refers to projects related to primary health care. The MINSA and CSS both with a 20% participation in ICT project, in addition we can notice the dispersion of projects for hospitals, where each one is developing programs per their needs or priorities. The national information about ICT projects of Health, it has been notorious the state of dispersion and segmented of public health information. We consider that it is a natural consequence of Policy in Panamanian Health System. This situation limits the information retrieval and knowledge of ICT in Health of Panama. To stakeholders, this information is directed so that health policies are designed towards a more effective and integral management, administering the ICT's as tools for the well-being of most the Panamanian population, including indigenous group.

A New mHealth App for Monitoring and Awareness of Healthy Eating: Development and User Evaluation by Spanish Users.

Modern-day society has moved towards a more sedentary lifestyle. Advances in technology and changes in habits in our daily lives have led a large part of the population towards a spiralling sedentary lifestyle and obesity. The main objective of this work is to develop and subsequently assess a mobile app, named DietApp, that provides advice about obtaining a healthy diet according to age, clinical history and physical condition. DietApp has been developed for iOS and Android systems, and a survey comprising 7 simple questions enabled the app to be evaluated on a user level by taking into account aspects such as its usefulness and ease of use. DietApp was assessed by 150 Spanish individuals between 18 and 69 years of age, and 84% of them thought it was easy to use. 80% of users also considered the dietary suggestions provided by the app to be very useful while 62% were of the opinion that it is very useful in general. All of them would recommend the app to other users. During the six months when the app was used, any dietary excess or shortcomings were corrected in 72% of those interviewed. A mobile app has been created that is easy to use and attractive, providing personalised suggestions according to illness that are useful for the individual.

mHealth App for iOS to Help in Diagnostic Decision in Ophthalmology to Primary Care Physicians.

Decision support systems (DSS) are increasingly demanded due that diagnosis is one of the main activities that physicians accomplish every day. This fact seems critical when primary care physicians deal with uncommon problems belonging to specialized areas. The main objective of this paper is the development and user evaluation of a mobile DSS for iOS named OphthalDSS. This app has as purpose helping in anterior segment ocular diseases' diagnosis, besides offering educative content about ophthalmic diseases to users. For the deployment of this work, firstly it has been used the Apple IDE, Xcode, to develop the OphthalDSS mobile application using Objective-C as programming language. The core of the decision support system implemented by OphthalDSS is a decision tree developed by expert ophthalmologists. In order to evaluate the Quality of Experience (QoE) of primary care physicians after having tried the OphthalDSS app, a written inquiry based on the Likert scale was used. A total of 50 physicians answered to it, after trying the app during 1 month in their medical consultation. OphthalDSS is capable of helping to make diagnoses of diseases related to the anterior segment of the eye. Other features of OphthalDSS are a guide of each disease and an educational section. A 70% of the physicians answered in the survey that OphthalDSS performs in the way that they expected, and a 95% assures their trust in the reliability of the clinical information. Moreover, a 75% of them think that the decision system has a proper performance. Most of the primary care physicians agree with that OphthalDSS does the function that they expected, it is a user-friendly and the contents and structure are adequate. We can conclude that OphthalDSS is a practical tool but physicians require extra content that makes it a really useful one.

Proposing Telecardiology Services on Cloud for Different Medical Institutions: A Model of Reference.

INTRODUCTION: For a cloud-based telecardiology solution to be established in any scenario, it is necessary to ensure optimum levels of security, as patient's data will not be in the same place from where access is gained. The main objective of this article is to present a secure, cloud-based solution for a telecardiology service in different scenarios: a hospital, a health center in a city, and a group of health centers in a rural area. METHODS: iCanCloud software is used to simulate the scenarios. The first scenario will be a city hospital with over 220,000 patients at its emergency services, and ∼1 million outpatient consultations. For the health center in a city, it serves ∼107,000 medical consultations and 16,700 pediatric consultations/year. In the last scenario, a group of health centers in a rural area serve an average 437.08 consultations/month and around 15.6 a day. RESULTS: Each one of the solutions proposed shares common features including the following: secure authentication through smart cards, the use of StorageGRID technology, and load balancers. For all cases, the cloud is private and the estimated price of the solution would cost around 450 €/month. CONCLUSIONS: Thanks to the research conducted in this work, it has been possible to provide an adapted solution in the form of a telecardiology service for a hospital, city health center, and rural health centers that offer security, privacy, and robustness, and is also optimum for a large number of cloud requests.

Big Data in Health: a Literature Review from the Year 2005.

The information stored in healthcare systems has increased over the last ten years, leading it to be considered Big Data. There is a wealth of health information ready to be analysed. However, the sheer volume raises a challenge for traditional methods. The aim of this article is to conduct a cutting-edge study on Big Data in healthcare from 2005 to the present. This literature review will help researchers to know how Big Data has developed in the health industry and open up new avenues for research. Information searches have been made on various scientific databases such as Pubmed, Science Direct, Scopus and Web of Science for Big Data in healthcare. The search criteria were "Big Data" and "health" with a date range from 2005 to the present. A total of 9724 articles were found on the databases. 9515 articles were discarded as duplicates or for not having a title of interest to the study. 209 articles were read, with the resulting decision that 46 were useful for this study. 52.6 % of the articles used were found in Science Direct, 23.7 % in Pubmed, 22.1 % through Scopus and the remaining 2.6 % through the Web of Science. Big Data has undergone extremely high growth since 2011 and its use is becoming compulsory in developed nations and in an increasing number of developing nations. Big Data is a step forward and a cost reducer for public and private healthcare.

Monitoring and Follow-up of Chronic Heart Failure: a Literature Review of eHealth Applications and Systems.

In developed countries heart failure is one of the most important causes of death, followed closely by strokes and other cerebrovascular diseases. It is one of the major healthcare issues in terms of increasing number of patients, rate of hospitalizations and costs. The main aim of this paper is to present telemedicine applications for monitoring and follow-up of heart failure and to show how these systems can help reduce costs of administering heart failure. The search for e-health applications and systems in the field of telemonitoring of heart failure was pursued in IEEE Xplore, Science Direct, PubMed and Scopus systems between 2005 and the present time. This search was conducted between May and June 2015, and the articles deemed to be of most interest about treatment, prevention, self-empowerment and stabilization of patients were selected. Over 100 articles about telemonitoring of heart failure have been found in the literature reviewed since 2005, although the most interesting ones have been selected from the scientific standpoint. Many of them show that telemonitoring of patients with a high risk of heart failure is a measure that might help to reduce the risk of suffering from the disease. Following the review conducted, in can be stated that via the research articles analysed that telemonitoring systems can help to reduce the costs of administering heart failure and result in less re-hospitalization of patients.

Utility of a mHealth App for Self-Management and Education of Cardiac Diseases in Spanish Urban and Rural Areas.

Analyze the utility of a mobile health app named HeartKeeper in several groups of population and obtain conclusions to be applied to other similar apps. A questionnaire has been designed to evaluate the usage and utility of the HeartKeeper app. The questionnaire information was collected by collaborating cardiologists from 32 patients before and after they used the app. Patients were randomly selected with established quotas within interest groups, so that men and women, patients older or younger than 60 years old and patients living in urban or rural areas were equally represented. Using the appropriate statistical techniques we see that the HeartKeeper app was useful for patients as they qualify with 70 points (out of 100) the overall opinion of the app, it helps them remember more easily taking their pills with a mean improvement of 20.94 points (p < 0.001) and they perceive a global improvement of their health (8.28 points, p < 0.001). We also observe that these improvements do not depend, in general, on the area (urban or rural) where the patient comes from or on their sex. Although older patients needed more help to use the app and used it slightly less frequently, the improvements on several measures considered, such as remembering taking pills, breathing problems or trouble developing activities, depend significantly (p < 0.05) on age with older patients reporting higher improvements than younger ones. The results obtained with the sample of patients considered in this research prove the utility of the HeartKeeper app. This utility is similar in urban and rural areas and for patients of both sexes and, to some extent, depends on the age of the patient with older patients reporting slightly lower frequency of use but higher health improvements than younger ones.

A mobile decision support system for red eye diseases diagnosis: experience with medical students.

A good primary health care is the base for a better healthcare system. Taking a good decision on time by the primary health care physician could have a huge repercussion. In order to ease the diagnosis task arise the Decision Support Systems (DSS), which offer counselling instead of refresh the medical knowledge, in a profession where it is still learning every day. The implementation of these systems in diseases which are a frequent cause of visit to the doctor like ophthalmologic pathologies are, which affect directly to our quality of life, takes more importance. This paper aims to develop OphthalDSS, a totally new mobile DSS for red eye diseases diagnosis. The main utilities that OphthalDSS offers will be a study guide for medical students and a clinical decision support system for primary care professionals. Other important goal of this paper is to show the user experience results after OphthalDSS being used by medical students of the University of Valladolid. For achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android mobile application. Moreover, the Quality of Experience (QoE) has been evaluated by the students through the questions of a short inquiry. The app developed which implements the algorithm OphthalDSS is capable of diagnose more than 30 eye's anterior segment diseases. A total of 67 medical students have evaluated the QoE. The students find the diseases' information presented very valuable, the appearance is adequate, it is always available and they have ever found what they were looking for. Furthermore, the students think that their quality of life has not been improved using the app and they can do the same without using the OphthalDSS app. OphthalDSS is easy to use, which is capable of diagnose more than 30 ocular diseases in addition to be used as a DSS tool as an educational tool at the same time.

Security Recommendations for mHealth Apps: Elaboration of a Developer's Guide.

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.

Development, Technical, and User Evaluation of a Web Mobile Application for Self-Control of Diabetes.

OBJECTIVE: The main objective of this research was to develop and evaluate a Web-based mobile application (app) known as "Diario Diabetes" on both a technical and user level, by means of which individuals with diabetes may monitor their illness easily at any time and in any place using any device that has Internet access. METHODS: The technologies used to develop the app were HTML, CSS, JavaScript, PHP, and MySQL, all of which are an open source. Once the app was developed, it was evaluated on a technical level (by measuring loading times) and on a user level, through a survey. RESULTS: Different loading times for the application were measured, with it being noted that under no circumstances does this exceed 2 s. Usability was evaluated by 150 users who initially used the application. A majority (71%) of users used a PC to access the app, 83% considered the app's design to be attractive, 67% considered the tasks to be very useful, and 67% found it very easy to use. CONCLUSIONS: Although applications exist for controlling diabetes both at mobile virtual shops or on a research level, our app may help to improve the administration of these types of patients and they are the ones who will ultimately opt for one or the other. According to the results obtained, we can state that all users would recommend the app's use to other users.