Design and Development of a Mobile-Based Self-Care Application for Patients with Type 2 Diabetes.

Introduction: Mobile-based applications play a leading role in changes in life-style, improve medication adherence, and provide a unique opportunity to aid patients with type 2 diabetes mellitus (T2DM) elevate their healthcare level. Therefore, we aim to design and develop a mobile-based self-care application for patients with T2DM.

Methods: The present study was an applied and developmental study to design and develop a mobile-based self-care application for people living with T2DM conducted in 2020.

Identifying features of a mobile-based application for self-care of people living with T2DM.

Introduction: Diabetes self-care requires support to empower patients to improve self-monitoring and maintain the necessary self-care behaviors. We aimed to identify features of a mobile-based application as a technology-based device for self-care of people living with T2DM.

Method: This study was conducted in two main phases in 2020.

A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved.