With the advent of artificial intelligence and Big Data-projects, the necessity for a transition
from analog medicine to modern-day solutions such as cloud computing becomes …

Background Although agricultural health has gained importance, to date, much of the
existing research relies on traditional epidemiological approaches that often face limitations …

Federated learning enables collaboration in medicine, where data is scattered across
multiple centers without the need to aggregate the data in a central cloud. While, in general …

This research is a quantitative research conducted in class V SD Gugus Wijaya Kusuma.
The purpose of this study was to determine the effect of Digital Learning Media on the …

Artificial intelligence (AI) and data sharing go hand in hand. In order to develop powerful AI
models for medical and health applications, data need to be collected and brought together …

Background: The question of the utility of face masks in preventing acute respiratory
infections has received renewed attention during the COVID-19 pandemic. However, given …

Abstract This ISPOR Good Practices report provides a framework for assessing the suitability
of electronic health records data for use in health technology assessments (HTAs). Although …

Pancreatic cancer is the seventh leading cause of cancer death in both sexes. The aim of
this study is to analyze baseline CT body composition using artificial intelligence to identify …

Problem Direct application of digital health technologies from high-income settings to low-
and middle-income countries may be inappropriate due to challenges around data …

In recent years, decentralized machine learning has emerged as a significant advancement
in biomedical applications, offering robust solutions for data privacy, security, and …