Visual Patient technology is a situation awareness-oriented visualization technology that translates numerical and waveform patient monitoring data into a new user-centered visual language. Vital sign values are converted into colors, shapes, and rhythmic movements-a language humans can easily perceive and interpret-on a patient avatar model in real time. In this review, we summarize the current state of the research on the Visual Patient, including the technology, its history, and its scientific context. We also provide a summary of our primary research and a brief overview of research work on similar user-centered visualizations in medicine. In several computer-based studies under various experimental conditions, Visual Patient transferred more information per unit time, increased perceived diagnostic certainty, and lowered perceived workload. Eye tracking showed the technology worked because of the way it synthesizes and transforms vital sign information into new and logical forms corresponding to the real phenomena. The technology could be particularly useful for improving situation awareness in settings with high cognitive demand or when users must make quick decisions. This comprehensive review of Visual Patient research is the foundation for an evaluation of the technology in clinical applications, starting with a high-fidelity simulation study in early 2020.
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http://dx.doi.org/10.3390/s20072112 | DOI Listing |
Transl Vis Sci Technol
January 2025
Department of Ophthalmology, University Hospital Bonn, Bonn, Germany.
Purpose: To compare a novel high-resolution optical coherence tomography (OCT) with improved axial resolution (High-Res OCT) with conventional spectral-domain OCT (SD-OCT) with regard to their capacity to characterize the disorganization of the retinal inner layers (DRIL) in diabetic maculopathy.
Methods: Diabetic patients underwent multimodal retinal imaging (SD-OCT, High-Res OCT, and color fundus photography). Best-corrected visual acuity and diabetes characteristics were recorded.
Invest Ophthalmol Vis Sci
January 2025
Department of Surgical Sciences, Eye Clinic Section, University of Turin, Turin, Italy.
Purpose: This study aimed to comprehensively assess visual performance in eyes with idiopathic epiretinal membrane (iERM). Additionally, it sought to explore the associations between optical coherence tomography (OCT) imaging biomarkers and visual performance in patients with iERM.
Methods: In this prospective, non-interventional study, 57 participants with treatment-naïve iERM from the University of Turin, between September 2023 and March 2024 were enrolled.
Insights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
Ultrasound J
January 2025
Department of Radiology, Hospital Universitari Vall d'Hebron, Passeig de la Vall d'Hebron, 119-129, 08035, Barcelona, Spain.
Background: Tele-robotic ultrasound (US) is a novel technique that might help overcome the current shortage of radiologists and poor access to radiologists and/or sonographers in remote or rural areas. Despite the promising results of this technology in the past two decades, there is still insufficient data about its advantages and limits, as well as the implementation in routine clinical practice and the learning curve for the user. The purpose of this prospective cohort-based study is to evaluate the performance of a 5G-based tele-robotic US system for abdominal and thyroid gland assessment in a cohort of healthy volunteers and outpatients, as well as assessing the learning curve and patient satisfaction.
View Article and Find Full Text PDFEgypt Heart J
January 2025
Department of Medicine, Western Michigan University, Kalamazoo, WV, USA.
Background: Patients on long-term dialysis for end-stage kidney disease have a high mortality rate, predominantly due to sudden cardiac death (SCD), which is associated with an increased risk of arrhythmias compared to the general population. Thus, the current systematic review and meta-analysis aimed to investigate the incidence of SCD among dialysis patients at risk of arrhythmia.
Methods: This systematic review and meta-analysis followed the PRISMA guidelines.
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