Zobrazeno 1 - 10 of 20 pro vyhledávání: '"Neha, Anegondi"'
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Akademický článek
Machine Learning to Predict Faricimab Treatment Outcome in Neovascular Age-Related Macular Degeneration
Autor: Yusuke Kikuchi, PhD, Michael G. Kawczynski, MS, Neha Anegondi, MTech, Ales Neubert, PhD, Jian Dai, PhD, Daniela Ferrara, MD, PhD, Carlos Quezada-Ruiz, MD
Publikováno v: Ophthalmology Science, Vol 4, Iss 2, Pp 100385- (2024)
Purpose: To develop machine learning (ML) models to predict, at baseline, treatment outcomes at month 9 in patients with neovascular age-related macular degeneration (nAMD) receiving faricimab. Design: Retrospective proof of concept study. Participan
Externí odkaz: https://doaj.org/article/7fd559e79c8d4a6b9bcab58db5377c48
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2
Akademický článek
Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases
Autor: Yixuan Zou, Xuefeng Hou, Neha Anegondi, Mohammadreza Negahdar, Dorothy Cheung, Paula Belloni, Alex de Crespigny, Alexandre Fernandez Coimbra
Publikováno v: ERJ Open Research, Vol 9, Iss 5 (2023)
Background Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic valu
Externí odkaz: https://doaj.org/article/df885346bb274c64b06723dd75925756
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3
Akademický článek
Multi-ancestry GWAS analysis identifies two novel loci associated with diabetic eye disease and highlights APOL1 as a high risk locus in patients with diabetic macular edema.
Autor: Amy D Stockwell, Michael C Chang, Anubha Mahajan, William Forrest, Neha Anegondi, Rion K Pendergrass, Suresh Selvaraj, Jens Reeder, Eric Wei, Victor A Iglesias, Natalie M Creps, Laura Macri, Andrea N Neeranjan, Marcel P van der Brug, Suzie J Scales, Mark I McCarthy, Brian L Yaspan
Publikováno v: PLoS Genetics, Vol 19, Iss 8, p e1010609 (2023)
Diabetic retinopathy (DR) is a common complication of diabetes. Approximately 20% of DR patients have diabetic macular edema (DME) characterized by fluid leakage into the retina. There is a genetic component to DR and DME risk, but few replicable loc
Externí odkaz: https://doaj.org/article/5e260e67982f45a2b7579ec2725cc7d5
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4
Deep Learning to Predict Geographic Atrophy Area and Growth Rate from Multimodal Imaging
Autor: Neha, Anegondi, Simon S, Gao, Verena, Steffen, Richard F, Spaide, SriniVas R, Sadda, Frank G, Holz, Christina, Rabe, Lee, Honigberg, Elizabeth M, Newton, Julia, Cluceru, Michael G, Kawczynski, Thomas, Bengtsson, Daniela, Ferrara, Qi, Yang
Publikováno v: Ophthalmology Retina. 7:243-252
To develop deep learning models for annualized geographic atrophy (GA) growth rate prediction using fundus autofluorescence (FAF) images and spectral-domain OCT volumes from baseline visits, which can be used for prognostic covariate adjustment to in
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::388c96da0a556148af7955c3ccaeab91
https://doi.org/10.1016/j.oret.2022.08.018
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7
Correlation of Volume of Macular Edema with Retinal Tomography Features in Diabetic Retinopathy Eyes
Autor: Santosh Gopi Krishna Gadde, Arpita Kshirsagar, Neha Anegondi, Thirumalesh B. Mochi, Stephane Heymans, Arkasubhra Ghosh, Abhijit Sinha Roy
Publikováno v: Journal of Personalized Medicine; Volume 11; Issue 12; Pages: 1337
Journal of Personalized Medicine
Journal of Personalized Medicine, 11(12):1337. Multidisciplinary Digital Publishing Institute (MDPI)
Journal of Personalized Medicine, Vol 11, Iss 1337, p 1337 (2021)
Optical coherence tomography (OCT) enables the detection of macular edema, a significant pathological outcome of diabetic retinopathy (DR). The aim of the study was to correlate edema volume with the severity of diabetic retinopathy and response to t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9a2988206604bbd49514071a146c8e8
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8
A Prospective OCT Study of Rubella Retinopathy
Autor: Abhijit Sinha Roy, Hemant Anaspure, Anand Vinekar, Jyoti Matalia, Shwetha Mangalesh, K Bhujang Shetty, Neha Anegondi
Publikováno v: Ophthalmology Retina. 2:1235-1240
To analyze rubella retinopathy qualitatively and quantitatively in children diagnosed with congenital rubella syndrome (CRS) using a handheld spectral-domain (SD) OCT device.Prospective, cross-sectional, nonrandomized, comparative observational study
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1c96da2ab5073c1a123a52f89185607
https://doi.org/10.1016/j.oret.2018.06.003
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9
Predicting geographic atrophy growth rate from fundus autofluorescence images using deep neural networks
Autor: Verena Steffen, Qi Yang, Michael Kawczynski, Simon S. Gao, Neha Anegondi
Publikováno v: Multimodal Biomedical Imaging XVI.
Geographic atrophy (GA) is late-stage dry age-related macular degeneration (AMD). Improved predictors of GA progression would be useful in clinical trial design and may be relevant for clinical practice. The purpose of this study was to accurately pr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::03baf5aa4abbcb70f43ba7fa242da0e8
https://doi.org/10.1117/12.2575898
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