Diabetic eye diseases, particularly Diabetic Retinopathy, is the leading cause of vision loss worldwide and can be prevented by early diagnosis through annual eye-screenings. However, cost, health care disparities, cultural limitations, etc. are the main barriers against regular screening. Eye-screenings conducted in community events with native-speaking staffs can facilitate regular check-up and development of awareness among underprivileged communities compared to traditional clinical settings. However, there are not sufficient technology support for carrying out the screenings in community settings with collaboration from community partners using native languages. In this paper, we have proposed and discussed the development of our software framework, “Mobile Teleophthalmology in Community Settings (mTOCS)”, that connects the community partners with eye-specialists and the Health Department staffs of respective cities to expedite this screening process. Moreover, we have presented the analysis from our study on the acceptance of community-based screening methods among the community participants as well as on the effectiveness of mTOCS among the community partners. The results have evinced that mTOCS has been capable of providing an improved rate of eye-screenings and better health outcomes.

Retinal eye disease is the most common reason for visual deterioration. Long-term management and follow-up are critical to detect the changes in symptoms. Optical Coherence Tomography (OCT) is a non-invasive diagnostic tool for diagnosing and managing various retinal eye diseases. With the increasing desire for OCT image, the clinicians are suffering from the burden of time on the diagnostic and the treatment. In this study, an auto-grading diagnostic tool is proposed to divide the OCT image for the retinal disease classification. In this tool, the classification model implements convolutional neural networks (CNNs), and the model training is based on denoised OCT images. The tool can detect the uploaded OCT image and automatically generate a result of classification in the categories of Choroidal neovascularization (CNV), Diabetic macular edema (DME), multiple drusen, and Normal. The system will definitely improve the performance of retinal eye disease diagnosis and alleviate the burden on the medical system.

It is necessary for a cancer survivor to have good health behavior. Essential exercise and proper diet are helpful to decrease the risk of recurrence of the disease and the development of a new cancer type. People from low socioeconomic status are more likely to participate in risky health behaviors and have a higher chance of recurrence of cancer. It is important to have a motivational system for cancer survivors that motivates them to perform regular physical activities. In this article, we discuss the development of an mHealth system, which aims to increase physical activity in Native American populations with culturally appropriate motivational text and video messages. The system also includes an e-journal to monitor and maintain proper healthcare. We will also analyze the pilot data to evaluate the usability and the effectiveness of the system.