Accès ouvert
2026
article
OpenAlex
Vahid Mohammadzadeh, Tyler Davis, Esteban Morales, Diana Salazar Vega et autres
PURPOSE: To design a supervised deep learning (DL) model to detect glaucoma progression with serial optic disc photographs (DPs). DESIGN: A retrospective longitudinal cohort study. PARTICIPANTS: One thousand five hundred ten eyes (916 patients) with ≥2 years of follow-up and 2 pairs …
us
(code pays fourni par la source)
Accès ouvert
2024
article
OpenAlex
Abigail A. Lee, Ty J. Skyles, Jamie L. Jensen, Brandon Ord et autres
PURPOSE: Human papillomavirus (HPV) causes an estimated 300,000 high grade cervical dysplasias and 36,000 preventable cancers each year in the United States alone. Despite having a safe, effective and long lasting vaccine since 2006, the rate of uptake has been suboptimal, particularly …
us
(code pays fourni par la source)
Accès ouvert
2024
article
OpenAlex
Ty J. Skyles, H Stevens, Spencer C. Davis, Acelan M. Obray et autres
Background: Seasonal influenza vaccination rates are very low among teenagers. Objectives: We used publicly available data from the NIS-Teen annual national immunization survey to explore factors that influence the likelihood of a teen receiving their seasonal flu shot. Methods: Traditional stepwise multivariable …
us
(code pays fourni par la source)
Accès ouvert
2024
article
OpenAlex
Vahid Mohammadzadeh, Sean Wu, Sajad Besharati, Tyler Davis et autres
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progression with deep learning (DL). …
us
(code pays fourni par la source)
Accès ouvert
2023
article
OpenAlex
Vahid Mohammadzadeh, Leyan Li, Zhe Fei, Tyler Davis et autres
Purpose: To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Design: Longitudinal cohort study. Subjects: 7150 eyes (4232 patients), with ≥ 5 …
us
(code pays fourni par la source)
Accès ouvert
2023
article
OpenAlex
Vahid Mohammadzadeh, Sean M. Wu, Tyler Davis, Arvind Vepa et autres
AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up. METHODS: 3919 eyes (2259 patients) with ≥2 ODPs …
us
(code pays fourni par la source)
Accès ouvert
2023
article
OpenAlex
Ella Bouris, Tyler Davis, Esteban Morales, Lourdes Grassi et autres
This study describes the development of a convolutional neural network (CNN) for automated assessment of optic disc photograph quality. Using a code-free deep learning platform, a total of 2377 optic disc photographs were used to develop a deep CNN capable of determining …
us
(code pays fourni par la source)
Accès ouvert
2022
article
OpenAlex
Haroon Adam Rasheed, Tyler Davis, Esteban Morales, Zhe Fei et autres
Purpose: To report an image analysis pipeline, DDLSNet, consisting of a rim segmentation (RimNet) branch and a disc size classification (DiscNet) branch to automate estimation of the disc damage likelihood scale (DDLS).Design: Retrospective observational.Participants: RimNet and DiscNet were developed with 1208 and …
us
(code pays fourni par la source)
Accès ouvert
2022
article
OpenAlex
Haroon Adam Rasheed, Tyler Davis, Esteban Morales, Zhe Fei et autres
Purpose: Accurate neural rim measurement based on optic disc imaging is important to glaucoma severity grading and often performed by trained glaucoma specialists. We aim to improve upon existing automated tools by building a fully automated system (RimNet) for direct rim identification …
us
(code pays fourni par la source)
2022
conference-abstract
OpenAlex
Tyler Davis, Panayiotis Petousis, Davina Zamanzadeh, Keith C. Norris et autres
Background: Patients with rapid eGFR decline tend to progress to kidney failure. Automated tools can identify individuals at risk of severe kidney function decline and facilitate disease mitigation. We describe a machine learning model for predicting the risk of rapid eGFR decline …
us
(code pays fourni par la source)
2021
conference-abstract
OpenAlex
Susanne B. Nicholas, Robert W Follett, Theona T. Tacorda, Xiaoyan Wang et autres
Background: The SARS-CoV-2 pandemic accelerated health disparities in chronic kidney disease (CKD). Here, we describe risk factors and access to care surrogates (area deprivation index-ADI) for clinical outcomes among SARS-CoV-2-tested patients in the CURE-CKD Registry. Methods: We formed a COVID-19 Sub-Registry within …
us
(code pays fourni par la source)
2020
conference-abstract
OpenAlex
Davina Zamanzadeh, Panayiotis Petousis, Tyler Davis, Anders O. Garlid et autres
Background: Using machine learning (ML) approaches to impute missing data has not been explored in CKD progression. We investigated the utility of a data-driven imputation to improve downstream classifier prediction of rapid eGFR decline in the CURE-CKD registry. Methods: We analyzed CKD …
us
(code pays fourni par la source)