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Dissecting the effectiveness of deep features as metric of perceptual image quality.
Neural Netw
January 2025
Image Processing Lab., Universitat de València, 46980 Paterna, Spain. Electronic address:
There is an open debate on the role of artificial networks to understand the visual brain. Internal representations of images in artificial networks develop human-like properties. In particular, evaluating distortions using differences between internal features is correlated to human perception of distortion.
View Article and Find Full Text PDFThe intersection of digital health and artificial intelligence: Clearing the cloud of uncertainty.
Digit Health
January 2025
Independent Researcher, Calgary, Alberta, Canada.
Digital health (DH) and artificial intelligence (AI) in healthcare are rapidly evolving but were addressed synonymously by many healthcare authorities and practitioners. A deep understanding and clarification of these concepts are fundamental and a prerequisite for developing robust frameworks and practical guidelines to ensure the safety, efficacy, and effectiveness of DH solutions and AI-embedded technologies. Categorizing DH into technologies (DHTs) and services (DHSs) enables regulatory, HTA, and reimbursement bodies to develop category-specific frameworks and guidelines for evaluating these solutions effectively.
View Article and Find Full Text PDFPerceptual Disturbances and Disorders in the ICD-11: An Overview and a Proposal for Systematic Classification.
Brain Sci
January 2025
Department of Surgery, Section of Neurosurgery, University of Otago, Dunedin 9016, New Zealand.
The International Classification of Diseases (ICD) has been developed and edited by the World Health Organisation and represents the global standard for recording health information and causes of death. The ICD-11 is the eleventh revision and came into effect on 1 January 2022. Perceptual disturbances refer to abnormalities in the way sensory information is interpreted by the brain, leading to distortions in the perception of reality.
View Article and Find Full Text PDFRetinotopic biases in contextual feedback signals to V1 for object and scene processing.
Curr Res Neurobiol
June 2025
Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, 62 Hillhead Street, Glasgow, G12 8QB, United Kingdom.
Identifying the objects embedded in natural scenes relies on recurrent processing between lower and higher visual areas. How is cortical feedback information related to objects and scenes organised in lower visual areas? The spatial organisation of cortical feedback converging in early visual cortex during object and scene processing could be retinotopically specific as it is coded in V1, or object centred as coded in higher areas, or both. Here, we characterise object and scene-related feedback information to V1.
View Article and Find Full Text PDFA Systematic Review of Antibiotic Administration Incidents Involving Neuraxial Routes: Clinical Analysis, Contributing Factors and Prevention Approaches.
Pain Ther
January 2025
Department of Anaesthesia, Tawam Hospital, PO Box 15258, Al Ain, United Arab Emirates.
Introduction: This review aimed to investigate the inadvertent administration of antibiotics via epidural and intrathecal routes. The secondary objective was to identify the contributing human and systemic factors.
Methods: PubMed, Scopus and Google Scholar databases were searched for the last five decades (1973-2023).
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