Academic Articles & Research Papers

Digital health technology in clinical trials

Digital health technologies (DHTs) have brought several significant improvements to clinical trials, enabling real-world data collection outside of the traditional clinical context and more patient-centered approaches. DHTs, such as wearabl...

Health technology in perspective

The ongoing development of information and communication technology (ICT) is taking the healthcare industry to the next level. It allows an independent healthcare system by which anyone can easily obtain tne real-time measurement of individ...

Bibliometric Analysis of Health Technology Research: 1990~2020

This paper aims to summarize the publishing trends, current status, research topics, and frontier evolution trends of health technology between 1990 and 2020 through various bibliometric analysis methods. In total, 6663 articles retrieved f...

Health Technology Assessment for Cardiovascular Digital Health Technologies and Artificial Intelligence: Why Is It Different?

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

BACKGROUND: Digital health technologies (ie, the integration of digital technology and health information) aim to increase the efficiency of health care delivery; they are rapidly adapting to health care contexts to provide improved medical...

Development of an evaluation framework for health information communication technology in contemporary pharmacy practice

Background: Health information communication technology (ICT) has rapidly evolved in contemporary pharmacy practice worldwide. The Australian healthcare system is experiencing a paradigm shift to real-time interconnectivity for practitioner...

Health technology, quality and safety in a learning health system

Health technology quality and safety is an important issue for health informatics (i.e. digital health) professionals. Health technologies have been used to (1) collect data that can be analyzed to improve the quality and safety of healthca...

Barriers and facilitators to utilizing digital health technologies by healthcare professionals

Abstract Digital technologies change the healthcare environment, with several studies suggesting barriers and facilitators to using digital interventions by healthcare professionals (HPs). We consolidated the evidence from existing systemat...

Digital health technologies: opportunities and challenges in rheumatology

Critical Perspectives on Digital Health Technologies

Abstract Discussions of digital health technologies in the popular media and the medical and public health academic literature frequently comment on how these technologies might offer new or improved ways of delivering health care, conducti...

Exploring barriers and enablers to implementing a digital mental health crisis risk mitigation pathway in acute paediatric care: A multi-site, exploratory mixed-methods study

Objective Children and young people (CYP) presenting in mental health crisis to acute paediatric settings represent a growing clinical and system-level challenge. These environments, primarily designed for physical healthcare, frequently la...

Hackathons as Stepping Stones in Health Care Innovation: Case Study With Systematic Recommendations

BackgroundUntil recently, developing health technologies was time-consuming and expensive, and often involved patients, doctors, and other health care professionals only as passive recipients of the end product. So far, users have been mini...

Artificial neural network–based model for sleep quality prediction for frontline medical staff during major medical assistance

Background: The sleep quality of medical staff was severely affected during COVID-19, but the factors influencing the sleep quality of frontline staff involved in medical assistance remained unclear, and screening tools for their sleep qual...

Comparative assessment of patient education content generated by five large language models on post-stroke complications: A cross-sectional study of safety, accuracy, reliability, readability, and empathy

Objective To compare the safety, accuracy, reliability, readability, and empathy of patient education content generated by five large language models (LLMs) for post-stroke complications. Methods This CHART-guided cross-sectional comparativ...

Mobile health approaches to disease surveillance in Africa; Wellvis COVID triage tool

COVID-19 has rapidly spread across the globe and was declared a pandemic by the World Health Organization (WHO). The COVID-19 infection continues to spread across Africa. In Africa, mobile phone applications have been used for the surveilla...

Digital quality gradient and the burden of elderly depression: A spatial multi kernel SVR analysis of socio economically vulnerable groups in England

Digital infrastructure is increasingly understood as part of the contemporary built environment and as a policy-relevant area-level correlate of older adults’ mental health. Existing studies have often relied on linear models and have paid ...

Challenges and conditions for successfully implementing and adopting the telematics infrastructure in German outpatient healthcare: A qualitative study applying the NASSS framework

Background Germany's healthcare system provides high-quality, universal health coverage to almost all residents. However, a major challenge lies in the strong separation of healthcare structures, which hinders efficient interprofessional an...

Artificial intelligence–aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs

Objective The aim of this study was to develop an artificial intelligence–based model to detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and chest X-ray (CXR) data. Method The transfer learning method w...

Application Strategies for Artificial Intelligence–based Clinical Decision Support System: From the Simulation to the Real-World

Exploring feature selection and classification methods for predicting heart disease

Machine learning has been used successfully to improve the accuracy of computer-aided diagnosis systems. This paper experimentally assesses the performance of models derived by machine learning techniques by using relevant features chosen b...