Mobile Decision Support Research Articles

Mobile decision support system with dynamic knowledge base using decision tree and case-based reasoning

Muslims from around the world performing Hajj and Umrah every year. While performing the ritual, pilgrims might encounter some problems that need an immediate solution, especially those related to do's and do not's in the ihram. The best way to get the solution is by referring to the Hajj Guider. However, they're limited and not available all the time. We proposed a dynamic knowledge-based approach that can capture possible problems and solutions from the expert on mobile platform. The knowledge is stored digitally that enable the pilgrims to refer it anytime and anywhere. Users can query both simple and advance questions to the system. The system has been implemented using an artificial intelligence method of decision tree and case-based reasoning methodology. We use case-based reasoning to retrieve similar cases (question and answer). Decision tree with dynamic knowledge based is being used to predict the solutions for problems inquired by users.

Mobile Decision Support System with Dynamic Knowledge Base using Decision Tree and Case-Based Reasoning

Muslims from around the world performing Hajj and Umrah every year. While performing the ritual, pilgrims might encounter some problems that need an immediate solution, especially those related to do's and do not's in the ihram. The best way to get the solution is by referring to the Hajj Guider. However, they're limited and not available all the time. We proposed a dynamic knowledge-based approach that can capture possible problems and solutions from the expert on mobile platform. The knowledge is stored digitally that enable the pilgrims to refer it anytime and anywhere. Users can query both simple and advance questions to the system. The system has been implemented using an artificial intelligence method of decision tree and case-based reasoning methodology. We use case-based reasoning to retrieve similar cases (question and answer). Decision tree with dynamic knowledge based is being used to predict the solutions for problems inquired by users.

A mobile and web-based clinical decision support and monitoring system for diabetes mellitus patients in primary care: a study protocol for a randomized controlled trial

BackgroundPhysicians’ guideline use rates for diagnosis, treatment and monitoring of diabetes mellitus (DM) is very low. Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support and monitoring systems (CDSMS) provides an effective solution to these problems. The purpose of the study is to develop a user-friendly, comprehensive, fully integrated web and mobile-based Clinical Decision Support and Monitoring System (CDSMS) for the screening, diagnosis, treatment, and monitoring of DM diseases which is used by physicians and patients in primary care and to determine the effectiveness of the system.MethodsThe CDSMS will be based on evidence-based guidelines for DM disease. A web and mobile-based application will be developed in which the physician will remotely monitor patient data through mobile applications in real time.The developed CDSMS will be tested in two stages. In the first stage, the usability, understandability, and adequacy of the application will be determined. Five primary care physicians will use the developed application for at least 16 DM patients. Necessary improvements will be made according to physician feedback. In the second phase, a parallel, single-blind, randomized controlled trial will be implemented. DM diagnosed patients will be recruited for the CDSMS trial by their primary care physicians. Ten physicians and their 439 patients will be involved in the study. Eligible participants will be assigned to intervention and control groups with simple randomization. The significance level will be accepted as p < 0.05. In the intervention group, the system will make recommendations on patient monitoring, diagnosis, and treatment. These recommendations will be implemented at the physician’s discretion. Patients in the control group will be treated by physicians according to current DM treatment standards. Patients in both groups will be monitored for 6 months. Patient data will be compared between 0th and 6th month of the study. . Clinical and laboratory outcomes will be assessed in person while others will be self-assessed online.DiscussionThe developed system will be the first of its kind to utilize evidence based guidelines to provide health services to DM patients.Trial registrationClinicalTrials.gov NCT02917226. 28 September 2016.

Healthcare support for underserved communities using a mobile social media platform

Emerging digital technologies for healthcare information support have already contributed to reducing the digital divide among rural communities. Although mobile health (m-health) applications facilitate provision of support for treatment consultation in real-time, their substantial potential has not yet been operationalised for decision support to meet citizen demand in developing nations. Modern healthcare information access, especially in rural areas of developing countries, is critical to effective healthcare, since both information and expert opinions are limited. Mobile phone and social media penetration, however, is often extensive. In this paper, we design and evaluate an innovative mobile decision support system (MDSS) solution for rural citizens healthcare decision support and information dissemination.Developed using a design science approach, the instantiated artifact connects underserved rural patients in Bangladesh to general practitioners (GPs) – allowing GPs, based on queries and information support provided, to evaluate patient conditions virtually and provide answers for further diagnosis or treatment. A cloud platform using social media embodies health record information and is used with a rating technique that matches queries to profiled remote experts, participating asynchronously. A comprehensive evaluation of the MDSS artifact ensures its utility, efficacy, and reliability.

A new search-and-rescue service in the Mediterranean Sea: a demonstration of the operational capability and an evaluation of its performance using real case scenarios

Abstract. A new web-based and mobile decision support system (DSS) for search-and-rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. In addition to the website, dedicated applications for iOS and Android have been created to optimise the user experience on mobile devices. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind data provided, respectively, by the CMEMS and ECMWF. The modelling of the drifting objects is based on the leeway model, which parameterises the wind drag of an object using a series of coefficients. These coefficients have been measured in field experiments for different types of objects, ranging from a person in the water to a coastal freighter adrift. OCEAN-SAR provides the user with an intuitive interface to run simulations and to visualise their results using Google Maps. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea.

Community health workers’ experiences of mobile device-enabled clinical decision support systems for maternal, newborn and child health in developing countries

The objective of this review is to synthesize evidence on the experiences of community health workers (CHWs) of mobile device-enabled clinical decision support systems (CDSSs) interventions designed to support maternal newborn and child health (MNCH) in low-and middle-income countries.Specific objectives.

Proposed Framework for Mobile Decision Support Systems for Higher Learning Institutions

The vast amount of information brought about by the use of Information Technologies can sometimes pose a challenge to decision makers about the relevance and effectiveness of certain information. This paper proposes a Mobile Decision Support System (MDSS) suitable for Higher Learning institution. To arrive to the proposed design, researchers used traditional research techniques such a questionnaire and interview to understand the way decision makers operate in their respective organizations. Using four higher learning institutions located in Dar es Salaam as case study, data were collected, digitized and analyzed. Results showed that despite having access to computers and other forms of information technologies, most decision makers rely on tradition methods such word of mouth, document review and meetings to arrive to most of their decisions. Many participants expressed their skepticism on the state of the information and communication technologies (ICT) infrastructures as some turned to their subordinates and offline sources as their convenient ways to gather information.

Mechanisms of Change in Diet and Activity in the Make Better Choices 1 Trial.

The Make Better Choices 1 trial demonstrated that participants with unhealthy diet and activity behaviors who were randomized to increase fruits/vegetables and decrease sedentary leisure achieved greater diet and activity improvement than those randomized to change other pairs of eating and activity behaviors. Participants randomized to decrease saturated fat and increase physical activity achieved the least diet-activity improvement. This study examined which psychological mechanisms mediated the effects of the study treatments on healthy behavior change. Participants (n = 204) were randomized to 1 of 4 treatments: increase fruits/vegetables and physical activity; decrease saturated fat and sedentary leisure; decrease saturated fat and increase physical activity; increase fruits/vegetables and decrease sedentary leisure. Treatments provided 3 weeks of remote coaching supported by mobile decision support technology and financial incentives. Mediational analyses were performed to examine whether changes in positive and negative affect, and self-efficacy, stages of readiness to change, liking, craving and attentional bias for fruit/vegetable intake, saturated fat intake, physical activity, and sedentary leisure explained the impact of the treatments on diet-activity improvement. Greater diet-activity improvement in those randomized to increase fruits/vegetables and decrease sedentary leisure was mediated by increased self-efficacy (indirect effect estimate = 0.04; 95% bias corrected CI, 0.003-0.11). All treatments improved craving, stage of change and positive affect. Accomplishing healthy lifestyle changes for 3 weeks improves positive affect, increases cravings for healthy foods and activities, and enhances readiness to make healthy behavior changes. Maximal diet and activity improvement occurs when interventions enhance self-efficacy to make multiple healthy behavior changes. (PsycINFO Database Record

The Role of Nurses in E-Health: The MobiGuide Project Experience.

Leveraging the experience of the European project MobiGuide, this paper elaborates on the nurses' role in developing, delivering and evaluating e-health based services. We focus on the home monitoring of atrial fibrillation. Patients enrolled in our study are provided with a smartphone and an ECG sensor, and receive recommendations, reminders and alerts concerning medications and measurements that they should perform through a mobile decision support system that is constantly updated by a backend system. Patients' data are sent to health care personnel that may visualize them, and act accordingly. Nurses play a central role in such setting. After being involved in the design of the caregiver interface, they are responsible for the patients' enrollment phase (which includes patients' training), for the daily checking of incoming data, for the triage of patients' complaints, and for the final phase of the study where patients are interviewed about their experience with the system.

Stakeholders perspectives on paper-based and electronic clinical decision support systems in Malawi Africa

The objective of this paper is to explore the perceptions of key stakeholders involved and/or affected by existing paper-based decision support guidelines (known as Community Case Management (CCM)) and a proposed digitised mobile clinical decision support system (CDSS) of CCM in rural settings of Malawi, Africa. Data was collected using field notes and semi-structured interviews with 17 key stakeholders (i.e. clinical, technical, development aid support (NGO), government and community health workers both in Malawi, Europe and USA). Stakeholders provide a rich insight into the variety of both perceived benefits and challenges of the existing guidelines and the proposed electronic CDSS. It was found that all stakeholders believe that the CDSS will improve adherence to guidelines and subsequently result in better care for children. It is further envisioned that the time needed for administration with the current paper-based approach could be reduced using electronic, as opposed to manual, collation and sending of records. This paper acts to underpin the rationale and motivation for the development and rollout of an electronic CDSS to support community health workers in their assessment, classification and treatment of young children in rural settings in Malawi, Africa.

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.

Mobile decision support system

No abstract available.

A linguistic mobile Decision Support System based on fuzzy ontology to facilitate knowledge mobilization

The current development of the Semantic Web has created an increasing demand for methods and systems that can make use of imprecise information. As the amounts of data collected constantly grows, it will not be feasible to overlook imprecise data. We show that a combination of mobile technology and fuzzy ontology with group decision making support methods will facilitate a mobilization of knowledge, offering users a possibility to get decision making support through their mobile devices regardless of the context and location. In this paper, as an illustration and verification, a web platform and an Android application have been developed to help users to choose a suitable wine for different types of dinners.

Decision support systems and applications in ophthalmology: literature and commercial review focused on mobile apps.

The growing importance that mobile devices have in daily life has also reached health care and medicine. This is making the paradigm of health care change and the concept of mHealth or mobile health more relevant, whose main essence is the apps. This new reality makes it possible for doctors who are not specialist to have easy access to all the information generated in different corners of the world, making them potential keepers of that knowledge. However, the new daily information exceeds the limits of the human intellect, making Decision Support Systems (DSS) necessary for helping doctors to diagnose diseases and also help them to decide the attitude that has to be taken towards these diagnoses. These could improve the health care in remote areas and developing countries. All of this is even more important in diseases that are more prevalent in primary care and that directly affect the people's quality of life, this is the case in ophthalmological problems where in first patient care a specialist in ophthalmology is not involved. The goal of this paper is to analyse the state of the art of DSS in Ophthalmology. Many of them focused on diseases affecting the eye's posterior pole. For achieving the main purpose of this research work, a literature review and commercial apps analysis will be done. The used databases and systems will be IEEE Xplore, Web of Science (WoS), Scopus, and PubMed. The search is limited to articles published from 2000 until now. Later, different Mobile Decision Support System (MDSS) in Ophthalmology will be analyzed in the virtual stores for Android and iOS. 37 articles were selected according their thematic (posterior pole, anterior pole, Electronic Health Records (EHRs), cloud, data mining, algorithms and structures for DSS, and other) from a total of 600 found in the above cited databases. Very few mobile apps were found in the different stores. It can be concluded that almost all existing mobile apps are focused on the eye's posterior pole. Among them, the most intended are for diagnostic of diabetic retinopathy. The primary market niche of the commercial apps is the general physicians.

English

This research studies three aspects relating to farmers readiness for the proposed mobile phone information and trade system (MAITS) namely (a) farmer readiness to adopt newly proposed mobile information and trade system (b) key factors that affect farmers mobile decision support systems (c) farmers readiness to connect with mobile enterprise networks. These were investigated using a qualitative research method. After a careful selection of a set of questions, interviews were conducted with selected farmers from four cities of Pakistan including Lahore, Faisalabad, Vehari and Khanewal. The analysis revealed that farmers readiness to embrace new mobile phone information systems requires maximum level of optimism and innovativeness along with deal of the inhibiting factors which affect the readiness state; inhibiting factors in MAITS adoption comprised of uncertainty factors and current faulty existing system services; and there has been a complete consensus among the farmers to practice MAITS along with mobile decision support system because it can help them in crop planning, farm inputs (seeds, fertilizer, sprays etc), harvesting, transporting and trading. The findings of this study will provide guidance to the relevant organizations when considering readiness and barriers towards implementing of MAITS. The results of the study will give insight to many extension service and policy makers to understand what farmers actually need.

The Study on Fire Spreading Based on Mobile Agent and Grid Technology

In order to build a truly open OpenDSS and enhance the complexity of decision-making DSS for solving the problem of Fire spreading. a new model was given based on mobile Agent Open Decision Support System in grid environment. Making use of the intelligence of MAS and adaptive capacity, based on the reasoning mechanisms for task decomposition and resource decision-making grid matching, described in detail layer program CBR-based reasoning mechanism of the Agent and its operation flow and interactive mechanism, put the complexity of distribution of decision-making problem solving to the grid nodes on the environment, implementation of parallel asynchronous decision-making problem solving. Optimize distribution through the logistics of the problem MABODSS design, it proved to improve the system's intelligence and operational efficiency.

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system.

Personal Decision Support Mobile Service for Extreme Situations

This article discusses aspects of implementation of a massive personal decision support mobile service for evacuation process in extreme situations, based on cloud computation platform CLAVIRE and a virtual society model. The virtual society model was constructed using an agent-based approach. To increase credibility the individual motivation methods (personal decision support and user training) were used.

Best Practice Differential Diagnosis iPhone app Best Practice Differential Diagnosis iPhone app

This updated iPhone app from the BMJ Group’s Best Practice series provides information in plain English to help healthcare professionals ‘reach an accurate diagnosis quickly and efficiently by providing essential mobile decision support information’.

Context-based mobile GeoBI: enhancing business analysis with contextual metrics/statistics and context-based reasoning

Business professionals are increasingly mobile and should be supported by suitable mobile Decision Support Systems (DSS). In our previous work, we have established that such suitable mobile DSS should be (i) GeoBI(Geospatial Business Intelligence)-enabled and (ii) context-based, and have addressed issues regarding context characterization and context modeling. The present paper deals with mobile GeoBI context-based reasoning. Through realistic scenarios, it highlights (i) the requirement for context-based reasoning to enhance mobile GeoBI experience, (ii) the need for contextual metrics/statistics to help mobile business professionals discover their local context, (iii) the need for crossing business performance metrics with contextual metrics to help mobile business professionals in discovering the context hidden behind business performance figures, and proposes convenient solutions to tackle these needs.