Research graph
References from Augmenting Kalman Filter Machine Learning Models with Data from OCT to Predict Future Visual Field Loss. Local targets link to admitted publications; unresolved targets remain external evidence.
Kalman filtering for spacecraft attitude estimation
10.2514/3.56190 · 1982 · External reference
Personalized state-space modeling of glucose dynamics for type 1 diabetes using continuously monitored glucose, insulin dose, and meal intake: an extended Kalman filter approach
10.1177/1932296814524080 · 2014 · External reference
The unscented Kalman filter estimates the plasma insulin from glucose measurement
10.1016/j.biosystems.2010.09.012 · 2011 · External reference
Using filtered forecasting techniques to determine personalized monitoring schedules for patients with open-angle glaucoma
10.1016/j.ophtha.2014.02.021 · 2014 · External reference
Accuracy of Kalman filtering in forecasting visual field and intraocular pressure trajectory in patients with ocular hypertension
10.1001/jamaophthalmol.2019.4190 · 2019 · External reference
Using Kalman filtering to forecast disease trajectory for patients with normal tension glaucoma
10.1016/j.ajo.2018.10.012 · 2019 · External reference
Study design and methods and baseline characteristics of study patients
10.1016/0197-2456(94)90046-9 · 1994 · External reference
The collaborative initial glaucoma treatment study: study design, methods, and baseline characteristics of enrolled patients
10.1016/s0161-6420(99)90147-1 · 1999 · External reference
The Ocular Hypertension Treatment Study: design and baseline description of the participants
10.1001/archopht.117.5.573 · 1999 · External reference
Trends in use of ancillary glaucoma tests for patients with open-angle glaucoma from 2001 to 2009
10.1016/j.ophtha.2011.09.045 · 2012 · External reference
The African Descent and Glaucoma Evaluation Study (ADAGES): design and baseline data
10.1001/archophthalmol.2009.187 · 2009 · External reference
Identifying glaucomatous vision loss with visual-function–specific perimetry in the Diagnostic Innovations in Glaucoma Study
10.1167/iovs.05-1546 · 2006 · External reference
Ensuring fairness in machine learning to advance health equity
10.7326/m18-1990 · 2018 · External reference
Implementing machine learning in health care—addressing ethical challenges
10.1056/nejmp1714229 · 2018 · External reference
Race/ethnic differences in the associations of the Framingham risk factors with carotid IMT and cardiovascular events
10.1371/journal.pone.0132321 · 2015 · External reference
Putting the data before the algorithm in big data addressing personalized healthcare
10.1038/s41746-019-0157-2 · 2019 · External reference
Reporting of demographic data and representativeness in machine learning models using electronic health records
10.1093/jamia/ocaa164 · 2020 · External reference
Unresolved reference
2012 · External reference
Comparing perimetric loss at different target intraocular pressures for patients with high-tension and normal-tension glaucoma
10.1016/j.ogla.2020.09.009 · 2021 · External reference
Maximum likelihood from incomplete data via the EM algorithm
10.1111/j.2517-6161.1977.tb01600.x · 1977 · External reference
Modelling series of visual fields to detect progression in normal-tension glaucoma
10.1007/bf00184085 · 1995 · External reference
Unresolved reference
2013 · External reference
The repeatability of mean defect with size III and size V standard automated perimetry
10.1167/iovs.12-10299 · 2013 · External reference
Rates of glaucomatous visual field change in a large clinical population
10.1167/iovs.14-14643 · 2014 · External reference
The relationship between nerve fiber layer and perimetry measurements
10.1167/iovs.06-0688 · 2007 · External reference
Correlation of retinal nerve fiber layer thickness and visual fields in glaucoma: a broken stick model
10.1016/j.ajo.2014.01.014 · 2014 · External reference
The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change
10.1167/iovs.12-10345 · 2012 · External reference
Time lag between functional change and loss of retinal nerve fiber layer in glaucoma
10.1167/iovs.61.13.5 · 2020 · External reference
Racial variations in the prevalence of primary open-angle glaucoma: the Baltimore Eye Survey
10.1001/jama.1991.03470030069026 · 1991 · External reference
The Barbados Eye Study: prevalence of open angle glaucoma
10.1001/archopht.1994.01090180121046 · 1994 · External reference
Prevalence of glaucoma in an urban West African population: the Tema Eye Survey
10.1001/jamaophthalmol.2013.1686 · 2013 · External reference
