The Journey of Zanzibar's Digitally Enabled Community Health Program to National Scale: Implementation Report.

Background: While high-quality primary health care services can meet 80%-90% of health needs over a person's lifetime, this potential is severely hindered in many low-resource countries by a constrained health care system. There is a growing consensus that effectively designed, resourced, and managed community health worker programs are a critical component of a well-functioning primary health system, and digital technology is recognized as an important enabler of health systems transformation.

Objective: In this implementation report, we describe the design and rollout of Zanzibar's national, digitally enabled community health program-Jamii ni Afya.

Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries.

As anyone who has witnessed firsthand knows, healthcare delivery in low-resource settings is fundamentally different from more affluent settings. Artificial Intelligence, including Machine Learning and more specifically Deep Learning, has made amazing advances over the past decade. Significant resources are now dedicated to problems in the field of medicine, but with the potential to further the digital divide by neglecting underserved areas and their specific context.

Analysis of User Interaction with a Brain-Computer Interface Based on Steady-State Visually Evoked Potentials: Case Study of a Game.

This paper presents a systematic analysis of a game controlled by a Brain-Computer Interface (BCI) based on Steady-State Visually Evoked Potentials (SSVEP). The objective is to understand BCI systems from the Human-Computer Interface (HCI) point of view, by observing how the users interact with the game and evaluating how the interface elements influence the system performance. The interactions of 30 volunteers with our computer game, named "Get Coins," through a BCI based on SSVEP, have generated a database of brain signals and the corresponding responses to a questionnaire about various perceptual parameters, such as visual stimulation, acoustic feedback, background music, visual contrast, and visual fatigue.

Effects of malnutrition on complication rates, length of hospital stay, and revenue in elective surgical patients in the G-DRG-system.

Objective: Malnutrition is known to independently affect patient outcomes. The aim of this study was to investigate the prevalence of patients at risk for malnutrition in an elective surgery patient cohort and to analyze the effects of malnutrition on morbidity, mortality, and hospital length of hospital (LOS). Furthermore, we aimed to evaluate the economic effect of a diligent coding of malnutrition, as a side diagnosis, in a simulation of the German Diagnosis-Related Group system.