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Background People with low health literacy experience more challenges in understanding instructions given by their health providers, following prescriptions, and understanding their health care system sufficiently to obtain the maximum benefits. People with insufficient health literacy have high risk of making medical mistakes, more chances of experiencing adverse drug effects, and inferior control of chronic diseases. Objective This study aims to design, develop, and evaluate a mobile health app, MediReader, to help individuals better understand complex medical materials and improve their health literacy. Methods MediReader is designed and implemented through several steps, which are as follows: measure and understand an individual’s health literacy level; identify medical terminologies that the individual may not understand based on their health literacy; annotate and interpret the identified medical terminologies tailored to the individual’s reading skill levels, with meanings defined in the appropriate external knowledge sources; evaluate MediReader using task-based user study and satisfaction surveys. Results On the basis of the comparison with a control group, user study results demonstrate that MediReader can improve users’ understanding of medical documents. This improvement is particularly significant for users with low health literacy levels. The satisfaction survey showed that users are satisfied with the tool in general. Conclusions MediReader provides an easy-to-use interface for users to read and understand medical documents. It can effectively identify medical terms that a user may not understand, and then, annotate and interpret them with appropriate meanings using languages that the user can understand. Experimental results demonstrate the feasibility of using this tool to improve an individual’s understanding of medical materials. 

The aging population worldwide is expected to increase the prevalence of Alzheimer's disease. As there is no medical curative treatment for this disease to date, alternative treatments have been applied to improve the patient's brain and general health. One of these efforts includes providing Alzheimer's patients with proper food and nutrition. In this paper, the authors propose a knowledge-powered personalized virtual coach to provide diet and nutrition assistance to patients of Alzheimer's and/or their informal caregivers. The virtual coach is built on top of an ontology-enhanced knowledge base containing knowledge about patients, Alzheimer's disease, food, and nutrition. Semantics-based searching and reasoning are performed on the knowledge base to get personalized context-aware recommendation and education about healthy eating for Alzheimer's patients. The proposed system has been implemented as a mobile application. Evaluation based on use cases has demonstrated the usefulness of this tool. 

Although social media and contents are being generated and shared with an unprecedented scale and speed, rural and underdeveloped areas throughout the world have only limited access due to the lack of high-speed Internet. Connecting rural communities to the digital world and providing them with right contents will provide the much-needed bridge between urban and rural areas. In this paper, we propose a communication and information framework that utilizes simple Internet of Things (IoT) in a rural community to assist delay-tolerant content distribution. Specifically, a hybrid fog-cloud content distribution network is constructed by deploying low-end simple fog nodes and utilizing the movement of community vehicles. Moreover, drones are used to distribute content on demand as a compliment of the delay tolerant network for better delivery rate and lower delay time. A novel drone scheduling algorithm is proposed to plan drones’ tours optimally. Extensive simulation experiments have been performed to evaluate the performance of the proposed framework.