Publicly Available Imaging Datasets for Age-related Macular Degeneration: Evaluation according to the Findable, Accessible, Interoperable, Reusable (FAIR) Principles.

Age-related macular degeneration (AMD), a leading cause of vision loss among older adults, affecting more than 200 million people worldwide. With no cure currently available and a rapidly increasing prevalence, emerging approaches such as artificial intelligence (AI) and machine learning (ML) hold promise for advancing the study of AMD. The effective utilization of AI and ML in AMD research is highly dependent on access to high-quality and reusable clinical data.

Use of artificial intelligence with retinal imaging in screening for diabetes-associated complications: systematic review.

Background: Artificial Intelligence (AI) has been used to automate detection of retinal diseases from retinal images with great success, in particular for screening for diabetic retinopathy, a major complication of diabetes. Since persons with diabetes routinely receive retinal imaging to evaluate their diabetic retinopathy status, AI-based retinal imaging may have potential to be used as an opportunistic comprehensive screening for multiple systemic micro- and macro-vascular complications of diabetes.

Methods: We conducted a qualitative systematic review on published literature using AI on retina images to detect systemic diabetes complications.

Multi-layered electrode constructs for neural tissue engineering.

Although neural tissue engineering holds great therapeutic potential for multiple clinical applications, one important challenge is the development of scaffolds that provide cues required for neural tissue development. To achieve this, biomaterial systems can be leveraged to present appropriate biological, mechanical, topographical and electrical cues that could direct cell fate. In this study, a multi-layered electrode construct was engineered to be used as a platform for 3D cell encapsulation for applications.

Synthesis and Polymerization of Thiophene-Bearing 2-Oxazolines and 2-Oxazines.

Intrinsically conductive polymers have garnered a great deal of attention for use in medical and bioelectronic applications. Despite this, challenges associated with the mechanical stability, processability, and fabrication of conducting polymers have limited their utility. To circumvent these limitations, thiophene substituted 2-oxazolines (2Ox) and 2-oxazines (2Ozi) are introduced, which can be polymerized to form a thermally stable and potentially melt-processable polymers as precursors for conductive polymers.

A toolbox for early detection of glass delamination in vials.

Glass delamination is a gradual process that may not become apparent until late in storage. Over the past three decades, it has been a leading cause of drug product recalls due to glass particulate contamination. The appearance of glass particles in the solution marks the final stage of glass delamination.

Complications associated with use of the Wolverine cutting balloon: insights from the Manufacturer and User Facility Device Experience (MAUDE) database.

Objectives: The Wolverine cutting balloon (CB) (Boston Scientific) is a specialized balloon catheter with microsurgical blades that is used for balloon-resistant lesions. The Manufacturer and User Facility Device Experience (MAUDE) database serves as a repository for reports of medical device complications. The aim of this study was to analyze complications associated with CB use during percutaneous coronary intervention in real-world contemporary practice.

Predictors of Health Care Disparities in Fuchs Dystrophy Treatment Using the IRIS Registry.

Purpose: To evaluate associations between sociodemographic factors and surgical management in patients with Fuchs Endothelial Corneal Dystrophy (FECD).

Methods: Patients >40 years old with FECD diagnosis and subsequent corneal edema between 2007 and 2020 were identified from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight). Multivariable Cox proportional hazards models were fit to examine the relationships between sociodemographic variables and time from FECD diagnosis to penetrating keratoplasty (PK) and endothelial keratoplasty (EK)/PK.

Deep Learning to Predict the Future Growth of Geographic Atrophy from Fundus Autofluorescence.

Purpose: The region of growth (ROG) of geographic atrophy (GA) throughout the macular area has an impact on visual outcomes. Here, we developed multiple deep learning models to predict the 1-year ROG of GA lesions using fundus autofluorescence (FAF) images.

Design: In this retrospective analysis, 3 types of models were developed using FAF images collected 6 months after baseline to predict the GA lesion area (segmented lesion mask) at 1.

Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.

Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset.

The association between adverse childhood experiences and adult cardiac function in the UK Biobank.

Aims: The importance of early life factors in determining health in later adulthood is increasingly recognized. This study evaluated the association of adverse childhood experiences (ACEs) with cardiovascular magnetic resonance (CMR) phenotypes.

Methods And Results: UK Biobank participants who had completed CMR and the self-reported questionnaire on traumatic childhood experiences were included.

Retinal Vessel Plexus Differentiation Based on OCT Angiography Using Deep Learning.

Purpose: Although structural OCT is traditionally used to differentiate the vascular plexus layers in OCT angiography (OCTA), the vascular plexuses do not always obey the retinal laminations. We sought to segment the superficial, deep, and avascular plexuses from OCTA images using deep learning without structural OCT image input or segmentation boundaries.

Design: Cross-sectional study.

Developing a 10-Layer Retinal Segmentation for MacTel Using Semi-Supervised Learning.

Purpose: Automated segmentation software in optical coherence tomography (OCT) devices is usually developed for and primarily tested on common diseases. Therefore segmentation accuracy of automated software can be limited in eyes with rare pathologies.

Methods: We sought to develop a semisupervised deep learning segmentation model that segments 10 retinal layers and four retinal features in eyes with Macular Telangiectasia Type II (MacTel) using a small labeled dataset by leveraging unlabeled images.

Review of Current and Future Medical Treatments in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a complex cancer requiring a multidisciplinary approach. For patients with locally or regionally advanced disease, surgery and/or radiation are the cornerstones of definitive treatment. Medical therapy plays an important adjunct role in this setting, typically consisting of a platinum-based regimen given as induction, concurrent, or adjuvant treatment.

Quality control of cardiac magnetic resonance imaging segmentation, feature tracking, aortic flow, and native T1 analysis using automated batch processing in the UK Biobank study.

Aims: Automated algorithms are regularly used to analyse cardiac magnetic resonance (CMR) images. Validating data output reliability from this method is crucial for enabling widespread adoption. We outline a visual quality control (VQC) process for image analysis using automated batch processing.

Impact of Loneliness and Social Support on Acute Health Service Use and Symptom Exacerbation Among Adults with Asthma and COPD.

Loneliness and low social support are associated with negative health outcomes among adults with asthma or COPD. Although social support is correlated with loneliness, low social support is neither necessary nor sufficient for the experience of loneliness. This study compares the relative association of loneliness and social support on symptom exacerbation (i.

Data Harmonization, Standardization, and Collaboration for Diabetic Retinal Disease (DRD) Research: Report From the 2024 Mary Tyler Moore Vision Initiative Workshop on Data.

The 2024 Mary Tyler Moore Vision Initiative (MTM Vision) Workshop on Data convened to discuss best practices and specific considerations for building a comprehensive, shareable MTM Vision data lake. The workshop aimed to accelerate the development of new indications, therapies, and regulatory pathways for diabetic retinal disease (DRD) by standardizing and harmonizing clinical data and ocular 'omics analyses. Standardization of data collection, the use of common data elements, and data interoperability were emphasized, alongside federated learning approaches to promote data sharing and collaboration while maintaining data privacy and security.

Emotion regulation among adults with asthma: Links with short-acting inhaler medication overuse and utilization of acute medical care.

Objective: Existing research suggests that emotion plays an important role in airway inflammation and asthma symptom control. The objective of this study was to determine whether difficulties regulating emotion were associated with overuse of short-acting inhaled medications and acute medical care usage in adults with asthma.

Methods: The sample included 401 adults with asthma recruited from an online panel of adults with chronic respiratory disease.

American Society of Retina Specialists Artificial Intelligence Task Force Report.

Since the Artificial Intelligence Committee of the American Society of Retina Specialists developed the initial task force report in 2020, the artificial intelligence (AI) field has seen further adoption of US Food and Drug Administration-approved AI platforms and significant development of AI for various retinal conditions. With expansion of this technology comes further areas of challenges, including the data sources used in AI, the democracy of AI, commercialization, bias, and the need for provider education on the technology of AI. The overall focus of this committee report is to explore these recent issues as they relate to the continued development of AI and its integration into ophthalmology and retinal practice.

Injectable conductive hydrogel electrodes for minimally invasive neural interfaces.

Soft bioelectronic neural interfaces have great potential as mechanically favourable alternatives to implantable metal electrodes. In this pursuit, conductive hydrogels (CHs) are particularly viable, combining tissue compliance with the required electrochemical characteristics. Physically-aggregated CHs offer an additional advantage by their facile synthesis into injectable systems, enabling minimally invasive implantation, though they can be impeded by a lack of control over their particle size and packing.

Myocardial Strain Measured by Cardiac Magnetic Resonance Predicts Cardiovascular Morbidity and Death.

Background: Myocardial strain using cardiac magnetic resonance (CMR) is a sensitive marker for predicting adverse outcomes in many cardiac disease states, but the prognostic value in the general population has not been studied conclusively.

Objectives: The goal of this study was to assess the independent prognostic value of CMR feature tracking (FT)-derived LV global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) metrics in predicting adverse outcomes (heart failure, myocardial infarction, stroke, and death).

Methods: Participants from the UK Biobank population imaging study were included.