About this Research Topic
Emerging technologies such as machine learning and immersive technologies (including virtual reality and augmented reality) hold great potential for driving disruptive healthcare innovation. However, the adoption of digital technology in healthcare, including use of data-driven tools in support of clinical decision-making and patient-facing applications relying on consumer electronic devices, is often hindered by issues of user experience, trust, equitability, and fairness. There is increasing recognition of a need to facilitate further convergence between the development of emerging technologies and user-centered design research for healthcare, with a view to achieving a positive impact on patients, care professionals, and the healthcare system.
This article collection addresses current development trends relating to user-centered digital healthcare innovation based on machine learning and immersive technologies, in order to identify opportunities associated with the deployment of new solutions in a range of environments – including clinical, domestic, and educational settings – and barriers to the adoption of technology by end users. A key aim is to identify opportunities for strengthening interdisciplinary collaboration as well as methods of lowering barriers and overcoming obstacles for the benefit of patients, care professionals, and the healthcare system. Examples of potential outcomes are effective design and use of solutions based on machine learning and immersive technologies to improve user experience, strategies to facilitate ethical development of digital technology for healthcare, and methods of encouraging adoption of advanced tools developed in line with principles of equitability and fairness.
Articles should address issues of user-centered digital healthcare innovation driven by machine learning and immersive technologies. Submissions should ideally be positioned at the intersection of digital technology development with user-centered design, although contributions more technical in nature as well as user experience studies are also welcome.
A non-exhaustive list of suitable topics and manuscript types is given below:
• Machine learning and/or immersive technologies (including augmented reality and virtual reality) for user-centered digital healthcare.
• Clinical decision support systems.
• Patient-facing applications.
• Tools for education and training of future medical professionals.
• Potential barriers to adoption of technology: issues of user experience, trust, equitability, and fairness in digital healthcare.
• Reviews and contributions discussing the development of intuitive, accessible, and inclusive digital interfaces.
• All aspects of healthcare that are being or have the potential to be impacted by machine learning and immersive technologies.
This article collection addresses current development trends relating to user-centered digital healthcare innovation based on machine learning and immersive technologies, in order to identify opportunities associated with the deployment of new solutions in a range of environments – including clinical, domestic, and educational settings – and barriers to the adoption of technology by end users. A key aim is to identify opportunities for strengthening interdisciplinary collaboration as well as methods of lowering barriers and overcoming obstacles for the benefit of patients, care professionals, and the healthcare system. Examples of potential outcomes are effective design and use of solutions based on machine learning and immersive technologies to improve user experience, strategies to facilitate ethical development of digital technology for healthcare, and methods of encouraging adoption of advanced tools developed in line with principles of equitability and fairness.
Articles should address issues of user-centered digital healthcare innovation driven by machine learning and immersive technologies. Submissions should ideally be positioned at the intersection of digital technology development with user-centered design, although contributions more technical in nature as well as user experience studies are also welcome.
A non-exhaustive list of suitable topics and manuscript types is given below:
• Machine learning and/or immersive technologies (including augmented reality and virtual reality) for user-centered digital healthcare.
• Clinical decision support systems.
• Patient-facing applications.
• Tools for education and training of future medical professionals.
• Potential barriers to adoption of technology: issues of user experience, trust, equitability, and fairness in digital healthcare.
• Reviews and contributions discussing the development of intuitive, accessible, and inclusive digital interfaces.
• All aspects of healthcare that are being or have the potential to be impacted by machine learning and immersive technologies.
Keywords: Machine learning, Artificial Intelligence, Immersive technologies, Healthcare innovation, Digital technology
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
