In 2000, the number of elderly citizens in the United States was 35 million, an increase of 3.7 million (11%) since 1990. Of these older adults, approximately 1.3 million (4%) have a low vision impairment. Older adults make up two-thirds of those diagnosed with a visual impairment. Low vision impairment, which is different from the typical vision changes associated with aging, occurs because of a chronic visual disorder that cannot be corrected medically, surgically, or with conventional eyeglasses, most often resulting in disability. The leading causes of low vision impairment are diabetic retinopathy, cataract, glaucoma, and age-related macular degeneration. Combined with the other physical changes associated with aging, the development of a low vision impairment further challenges the functional performance and safety of those 65 and older. Furthermore, the psychological impact from the physical changes accompanying aging is compounded for those with a low vision impairment. In response to the health needs of all age groups, Healthy People 2010 has established overarching goals to increase quality and years of healthy life and eliminate health disparities. An interdisciplinary course for allied health students was developed to support future health care providers in improving quality of life for older adults with low vision and help decrease health disparities in this population. This paper reports on the pilot experience with this course.
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Ophthalmic Physiol Opt
January 2025
Vision and Hearing Sciences Research Centre, Anglia Ruskin University, Cambridge, UK.
Purpose: Wearable electronic low vision enhancement systems (wEVES) improve visual function but are not widely adopted by people with vision impairment. Here, qualitative research methods were used to investigate the usefulness of wEVES for people with age-related macular degeneration (AMD) after an extended home trial.
Methods: Following a 12-week non-masked randomised crossover trial, semi-structured interviews were completed with 34 participants with AMD, 64.
J AAPOS
January 2025
Department of Binocular Vision Pathophysiology and Strabismus, Medical University of Lodz, University Barlicki Hospital No.1, Lodz, Poland.
Purpose: To determine the effect of low hypermetropia correction and orthoptic exercises on binocular visual function in children with symptomatic convergence insufficiency.
Methods: This was a prospective, randomized intervention with a 3-month follow-up. Consecutive pediatric patients with convergence insufficiency and hypermetropia who met inclusion criteria were randomly assigned to one of three treatment groups: spectacle correction and orthoptic training (group 1), spectacle correction alone (group 2) and orthoptic training alone (group 3).
Crit Rev Oncol Hematol
January 2025
Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA. Electronic address:
There is a much debate regarding optimal selection in patients with metastatic cancer who should undergo local treatment (surgery or radiation treatment) to the primary tumor and/or metastases. Additionally, the optimal treatment of newly diagnosed metastatic cancer is largely unclear. Current prognostication systems to best inform these clinical scenarios are limited, as all metastatic patients are grouped together as having Stage IV disease without further incorporation of patient and disease-specific covariates that significantly impact patient outcomes.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Power, Adama Science and Technology University, Adama, 1888, Ethiopia.
Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision.
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