Purpose: To develop a mobile app that allows capturing and editing of photographs, performs image transposition and projection of a protractor with 360° axis markings, and permits accurate visualization of programmed alignment for the positioning of toric intraocular lenses (IOLs).
Methods: In this prospective case series study, a codesign methodology was chosen to develop the Eye Axis Check application. After app development, measurements were obtained and comparisons were made between manual marks and toric IOL alignment without and with the app in 30 eyes that had undergone cataract surgery with toric IOLs. The mobile app was made available to 15 ophthalmic surgeons in different cities to assess its usability.
Results: The users approved the developed application for its ease of use and utility. The mean difference between the markings made manually and those made with the app was 1° (±2°; range: 0°-5°), and the mean difference between the IOL position and the assessment made by the app was 3° (±3°; range: 0°-12°). Upon comparison of the agreement between the app measurements and the manual measurements for the IOL angle, no significant differences were found, and an excellent concordance (0.997) and a strong positive linear correlation (0.995) were observed.
Conclusion: A mobile app for preoperative planning and intraoperative toric IOL alignment was developed and revealed to be useful and easy to use.
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http://dx.doi.org/10.1155/2020/8354140 | DOI Listing |
Sci Rep
January 2025
HeartMath Institute, Boulder Creek, CA, 95006, USA.
This global study analyzed data from the largest dataset ever studied in the Heart Rate Variability (HRV) biofeedback field, comprising 1.8 million user sessions collected from users of a mobile app during 2019 and 2020. We focused on HRV Coherence, which is linked to improved emotional stability and cognitive function.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Biomedical Engineering and the Institute of Materials Science, University of Connecticut, Storrs, CT, 06269, USA.
Wearable and implantable bioelectronics that can interface for extended periods with highly mobile organs and tissues across a broad pH range would be useful for various applications in basic biomedical research and clinical medicine. The encapsulation of these systems, however, presents a major challenge, as such devices require superior barrier performance against water and ion penetration in challenging pH environments while also maintaining flexibility and stretchability to match the physical properties of the surrounding tissue. Current encapsulation materials are often limited to near-neutral pH conditions, restricting their application range.
View Article and Find Full Text PDFNurse Educ Today
January 2025
School of Nursing and Midwifery, Deakin University, Burwood, Victoria 3125, Australia; Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Victoria, Australia.
Objective: To identify and synthesise existing literature about the use of mobile educational applications (apps) designed to enhance the learning experience of nurses and midwives.
Design: A narrative review using a systematic, structured and comprehensive search of the literature.
Data Sources: Medline Complete (EBSCO), CINAHL (EBSCO), ERIC (EBSCO) and Embase (OVID) electronic databases.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFAge Ageing
January 2025
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Background: A mobile cognition scale for community screening in cognitive impairment with rigorous validation is in paucity. We aimed to develop a digital scale that overcame low education for community screening for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and AD.
Methods: A mobile cognitive self-assessment scale (CogSAS) was designed through the Delphi process, which is feasible for the older population with low education.
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