Research on artificial intelligence (AI) for healthcare gained interest in recent years. However, the use of AI in daily clinical practice is still rare. We created and distributed an online survey among professionals working within the health informatics field to explore their views. The provided answers were classified into referring or not to: 1) Application areas; 2) Medical specialities; 3) Specific technologies; 4) Use cases; 5) Citizens involvement; and 6) Challenges. We received 42 valid responses. With regard to the sentiment of the answers, 71,4% were classified by the AFINN tool as being positive. In light of the open question, 76,2% of the respondents referred to possible applications areas. They think the most frequent uses will be for diagnostic, decision making and treatment. 54,8% of respondents referred to use cases, being personalized care and daily practice the most popular scenarios. 28,6% mentioned citizens' involvement, and 23,8% medical specialities in which AI might be used. There is a mostly positive attitude towards the application of AI in healthcare, in particular regarding its future use for realising routine tasks. From these results, we conclude that research should further focus on realising AI-based applications for relieving health professionals from repetitive tasks and optimize healthcare processes.
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http://dx.doi.org/10.3233/SHTI210301 | DOI Listing |
Annu Rev Neurosci
January 2025
Department of Cognitive and Psychological Sciences and Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA; email:
The twenty-first century has brought forth a deluge of theories and data shedding light on the neural mechanisms of motivated behavior. Much of this progress has focused on dopaminergic dynamics, including their signaling properties (how do they vary with expectations and outcomes?) and their downstream impacts in target regions (how do they affect learning and behavior?). In parallel, the basal ganglia have been elevated from their original implication in motoric function to a canonical circuit facilitating the initiation, invigoration, and selection of actions across levels of abstraction, from motor to cognitive operations.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Health Services Research Management, AI and Digital Health Lab (Centre for Healthcare Innovation Research), City St George's University, London, United Kingdom.
User trust is pivotal for the adoption of digital health systems interventions (DHI). In response, numerous trust-building guidelines have recently emerged targeting DHIs such as artificial intelligence. The common aim of these guidelines aimed at private sector actors and government policy makers is to build trustworthy DHI.
View Article and Find Full Text PDFTop Cogn Sci
January 2025
Department of Intelligence and Information, Seoul National University.
This study delves into how various musical factors influence the experience of auditory illusions, building on Diana Deutsch's scale illusion experiments and subsequent studies. Exploring the interaction between scale mode and timbre, this study assesses their influence on auditory misperceptions, while also considering the impact of an individual's musical training and ability to discern absolute pitch. Participants were divided into nonmusicians, musicians with absolute pitch, and musicians with relative pitch, and were exposed to stimuli modified across three scale modes (tonal, dissonant, atonal) and two timbres (same, different).
View Article and Find Full Text PDFJ Bras Pneumol
January 2025
. Methods in Epidemiologic, Clinical, and Operations Research-MECOR-program, American Thoracic Society/Asociación Latinoamericana del Tórax, Montevideo, Uruguay.
Sci Robot
January 2025
Department of Bioengineering, Imperial College of London, London, UK.
Despite the advances in bionic reconstruction of missing limbs, the control of robotic limbs is still limited and, in most cases, not felt to be as natural by users. In this study, we introduce a control approach that combines robotic design based on postural synergies and neural decoding of synergistic behavior of spinal motoneurons. We developed a soft prosthetic hand with two degrees of actuation that realizes postures in a two-dimensional linear manifold generated by two postural synergies.
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