Using Large Language Models for Efficient Cancer Registry Coding in the Real Hospital Setting: A Feasibility Study.

The primary challenge in reporting cancer cases lies in the labor-intensive and time-consuming process of manually reviewing numerous reports. Current methods predominantly rely on rule-based approaches or custom-supervised learning models, which predict diagnostic codes based on a single pathology report per patient. Although these methods show promising evaluation results, their biased outcomes in controlled settings may hinder adaption to real-world reporting workflows.

Social determinants of health as risk factors for keratoconus in the All of Us database.

Background/aims: Clinical risk factors for keratoconus (KCN) have previously been established. While the impact of the social determinants of health on the epidemiology and pathophysiology of KCN has been explored, further study of these associations is needed in large and diverse populations. This cross-sectional study determines how education level and income impact the prevalence of KCN in the USA using the National Institutes of Health 'All of Us' database.

LightDPH: Lightweight Dual-Projection-Head Hierarchical Contrastive Learning for Skin Lesion Classification.

Effective skin cancer detection is crucial for early intervention and improved treatment outcomes. Previous studies have primarily focused on enhancing the performance of skin lesion classification models. However, there is a growing need to consider the practical requirements of real-world scenarios, such as portable applications that require lightweight models embedded in devices.

The Association between Glaucoma Severity and Hip Fractures in California Medicare Beneficiaries.

Purpose: To examine the association between glaucoma severity and hip fractures in older adults.

Design: Retrospective cross-sectional study.

Subjects: California (CA) Medicare beneficiaries in 2019 with Parts A & B coverage.

A New Era of Ophthalmology Leadership? A Descriptive and Comparative Analysis of Ophthalmology Department Chairs in 2024.

Purpose: To (1) characterize and analyze the demographics and scholarly achievements of United States (US) academic ophthalmology department chairs, and (2) to elucidate trends in the academic and demographic profiles of newly hired department chairs.

Design: Cross-sectional study.

Methods: Online search of publicly available resources conducted January 1, 2024.

Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

Background: International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on human interpretation, which can be expensive, time consuming, and prone to errors. With the transition from the International Classification of Diseases, Ninth Revision, to the International Classification of Diseases, Tenth Revision (ICD-10), the coding process has become more complex, highlighting the need for automated approaches to enhance coding efficiency and accuracy. Inaccurate coding can result in substantial financial losses for hospitals, and a precise assessment of outcomes generated by a natural language processing (NLP)-driven autocoding system thus assumes a critical role in safeguarding the accuracy of the Taiwan diagnosis related groups (Tw-DRGs).

Associations between Statin Use and Glaucoma in the All of Us Research Program.

Purpose: To investigate associations between statin use and glaucoma in the 2017 to 2022 All of Us (AoU) Research Program.

Design: Cross-sectional, population-based.

Participants: 79 742 adult participants aged ≥40 years with hyperlipidemia and with electronic health record (EHR) data in the AoU database.

Racial and Ethnic Differences in the Prevalence and Treatment Patterns for Neovascular Glaucoma in the American Academy of Ophthalmology IRIS® Registry.

Purpose: To examine racial and ethnic differences in the prevalence and treatment patterns for neovascular glaucoma (NVG) in at-risk individuals in the American Academy of Ophthalmology (Academy) IRIS® Registry (Intelligent Research in Sight).

Design: Observational retrospective cohort study.

Participants: Eyes in the IRIS Registry with a retinal ischemia based on a history of proliferative diabetic retinopathy, retinal vein occlusion, and/or ocular ischemic syndrome.

Association of Open-Angle Glaucoma With Dementia in California Medicare Beneficiaries.

Purpose: To examine the associations between open-angle glaucoma (OAG) subtypes and dementia in 2019 California Medicare beneficiaries.

Design: Retrospective cross-sectional study.

Methods: OAG diagnosis was determined by the International Classification of Diseases, Tenth Revision (ICD-10), diagnosis codes in part B claims, including the following OAG subtypes: primary open-angle glaucoma (POAG), normal tension glaucoma (NTG), pseudoexfoliative glaucoma (PXG), and pigmentary glaucoma (PG).

Geographic Trends in Ophthalmology Resident Physician Compensation and Cost-of-Living Expenses.

Importance: Given that resident physician financial strain has been associated with poor outcomes, objective metrics to forecast financial well-being may be useful to (1) applicants when evaluating ophthalmology residency programs and (2) programs when determining resident benefits.

Objectives: To determine and compare the relative value of ophthalmology resident stipends plus benefits when adjusted for cost-of-living expenses and to analyze program characteristics associated with greater resident net incomes.

Design, Setting, And Participants: In this cross-sectional study, the American Medical Association's Fellowship and Residency Electronic Interactive Database was used to identify US Accreditation Council for Graduate Medical Education-accredited ophthalmology residency programs.

Deep Deblurring in Teledermatology: Deep Learning Models Restore the Accuracy of Blurry Images' Classification.

Blurry images in teledermatology and consultation increased the diagnostic difficulty for both deep learning models and physicians. We aim to determine the extent of restoration in diagnostic accuracy after blurry images are deblurred by deep learning models. We used 19,191 skin images from a public skin image dataset that includes 23 skin disease categories, 54 skin images from a public dataset of blurry skin images, and 53 blurry dermatology consultation photos in a medical center to compare the diagnosis accuracy of trained diagnostic deep learning models and subjective sharpness between blurry and deblurred images.

Automatic 3D left atrial strain extraction framework on cardiac computed tomography.

Background And Objective: Strain analysis provides insights into myocardial function and cardiac condition evaluation. However, the anatomical characteristics of left atrium (LA) inherently limit LA strain analysis when using echocardiography. Cardiac computed tomography (CT) with its superior spatial resolution, has become critical for in-depth evaluation of LA function.

Anti-Asian biases in federal grant reviews: Commentary on Yip et al. (2021).

Prior to the 2021 special issue "Rendered Invisible: Are Asian Americans a Model or a Marginalized Minority?" (Yip et al., 2021), only seven articles on Asian American, Native Hawaiian, and Pacific Islander (AANHPI) populations were published in the journal in 3 decades. The special issue interrogated sources of invisibility and marginalization of AANHPIs not only in the field of psychology but also in the broader national landscape.

Population-Level Associations Between Visual Impairment and Functional Difficulties in California.

Purpose: The prevalence of visual impairment is increasing, and there is a need to understand the functional implications. Using the American Community Survey (ACS) data, this study examined the relationship between visual impairment and functional difficulties in California.

Methods: Using the 2010-2014 and 2015-2019 ACS 5-year estimates from the U.

Machine-learning models are superior to severity scoring systems for the prediction of the mortality of critically ill patients in a tertiary medical center.

Background: Intensive care unit (ICU) mortality prediction helps to guide therapeutic decision making for critically ill patients. Several scoring systems based on statistical techniques have been developed for this purpose. In this study, we developed a machine-learning model to predict patient mortality in the very early stage of ICU admission.

A multi-label transformer-based deep learning approach to predict focal visual field progression.

Purpose: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression, which has not been explored in prior studies.

Methods: The study included 2430 eyes of 1283 patients with four or more consecutive VF examinations from the baseline.

Identifying a stable and generalizable factor structure of major depressive disorder across three large longitudinal cohorts.

The Patient Health Questionnaire 9 (PHQ-9) is the current standard outpatient screening tool for measuring and tracking the nine symptoms of major depressive disorder (MDD). While the PHQ-9 was originally conceptualized as a unidimensional measure, it has become clear that MDD is not a monolithic construct, as evidenced by high comorbidities with other theoretically distinct diagnoses and common symptom overlap between depression and other diagnoses. Therefore, identifying reliable and temporally stable subfactors of depressive symptoms could allow research and care to be tailored to different depression phenotypes.

Access to Eye Care Providers and Glaucoma Severity in the National Institutes of Health All of Us Research Program.

Prcis: In the "All of Us (AoU) Research Program," individuals with access to vision care were more likely to have mild, moderate, or severe glaucoma and undergo incisional surgery compared with those without vision care access.

Purpose: To examine the associations between access to eye care, glaucoma severity, and incisional glaucoma surgery using data from the National Institute of Health AoU Research Program.

Materials And Methods: Individuals with International Classification of Diseases Ninth or 10th Revision codes and who answered the survey question about eye care access in AoU were included in the study.

Predictors of Glaucomatous Progression in Individuals with Small and Large Optic Discs.

Purpose: To identify factors associated with glaucomatous progression in individuals with small and large optic discs.

Design: Retrospective review.

Subjects: 4505 individuals with glaucoma at UCLA; 233 (59.

Monitoring the Progression of Clinically Suspected Microbial Keratitis Using Convolutional Neural Networks.

Purpose: For this study, we aimed to determine whether a convolutional neural network (CNN)-based method (based on a feature extractor and an identifier) can be applied to monitor the progression of keratitis while managing suspected microbial keratitis (MK).

Methods: This multicenter longitudinal cohort study included patients with suspected MK undergoing serial external eye photography at the 5 branches of Chang Gung Memorial Hospital from August 20, 2000, to August 19, 2020. Data were primarily analyzed from January 1 to March 25, 2022.

Prevalence and Severity of Glaucoma in the California Medicare Population.

Purpose: To examine the prevalence of glaucoma by type and severity in the 2019 California (CA) Medicare population, and to identify associated demographic and systemic factors.

Design: Retrospective cross-sectional design.

Methods: The study population included all 2019 CA Medicare beneficiaries ≥65 years of age with Part A and Part B coverage.

Disparities in Glaucoma Surgery: A Review of Current Evidence and Future Directions for Improvement.

There is a need to understand existing disparities in glaucoma surgery and to create strategies to eliminate these disparities. Disparities can exist in several aspects of glaucoma surgical management, including patient selection and timing of surgery, type of surgery performed, intra-operative and postoperative surgical complications, follow-up surgical care, and long-term surgical outcomes. Additionally, multiple types of disparities can exist within each of these realms, including disparities by race and ethnicity, age, gender, insurance type, people with disabilities, and other social, economic, and demographic factors.

Outcomes of microPulse transscleral laser therapy in eyes with prior glaucoma aqueous tube shunt.

Purpose: To evaluate the outcomes of micropulse transscleral laser therapy (MP-TLT) in patients with uncontrolled glaucoma and prior glaucoma aqueous tube shunt.

Methods: In this single‑center, retrospective, interventional case series, eyes that underwent MP-TLT and had prior glaucoma aqueous tube shunt surgeries were included. The Cyclo Glaucoma Laser System (IRIDEX Corporation, Mountain View, CA, USA) with the MicroPulse P3 probe (version 1) was used.

Social Vulnerability, Prevalence of Glaucoma, and Incidence of Glaucoma Surgery in the California Medicare Population.

Purpose: To examine associations of Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index (SVI) scores with prevalence of glaucoma and incidence of glaucoma surgery in 2019 California Medicare beneficiaries.

Design: Retrospective cross-sectional study.

Participants: 2019 California Medicare beneficiaries ≥ 65 years old with part A and part B coverage.