https://www.selleckchem.com/Androgen-Receptor.html Diagnostics in many low- and middle-income countries are conducted through centralized laboratory networks. Samples are collected from patients at remote point-of-care health facilities, and diagnostic tests are performed at centralized laboratories. Sample transportation systems that deliver diagnostic samples and test results are crucial for timely diagnosis and treatment in such diagnostic networks. However, they often lack the timely and accurate data (eg, the quantity and location of samples prepared for collection) required for efficient operation. This study aims to demonstrate the feasibility, adoption, and accuracy of a distributed data collection system that leverages basic mobile phone technology to gather reports on the quantity and location of patient samples and test results prepared for delivery in the diagnostic network of Malawi. We designed a system that leverages unstructured supplementary service data (USSD) technology to enable health workers to submit daily reports describing the q any explicit financial incentives.[This corrects the article DOI 10.2196/23137.]. Women choosing a levonorgestrel-releasing intrauterine system may experience changes in their menstrual bleeding pattern during the first months following placement. Although health care professionals (HCPs) can provide counseling, no method of providing individualized information on the expected bleeding pattern or continued support is currently available for women experiencing postplacement bleeding changes. We aim to develop a mobile phone-based medical app (MyIUS) to meet this need and provide a digital companion to women after the placement of the intrauterine system. The MyIUS app is classified as a medical device and uses an artificial intelligence-based bleeding pattern prediction algorithm to estimate a woman's future bleeding pattern in terms of intensity and regularity. We developed the app with the help of a multidisciplinar