A hybrid artificial intelligence framework for glaucoma monitoring
A hybrid artificial intelligence framework for glaucoma monitoring
批准号:
9892013
负责人:
Tobias Elze
金额:
$22.08万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2022-03-31
关键词:
AcademyAddressAmericanArtificial IntelligenceAxonBayesian ModelingBig DataBig Data to KnowledgeBlindnessCaringClinicalClinical TrialsCommunitiesComplexComputer ModelsComputer softwareDataData AnalysesData AnalyticsData SetDetectionDevicesDiseaseDisease ProgressionEvolutionEyeGaussian modelGlaucomaGoalsHybridsInstitutesIntelligenceJointsJudgmentKnowledgeMachine LearningMeasurementMeasuresMethodsModelingModernizationMonitorNeurodegenerative DisordersOphthalmologyOptic NerveOptical Coherence TomographyOutcomePatientsPatternPopulationPreventionPublic HealthRegistriesResearchRetinaSeverity of illnessSourceStructural ModelsStructureSurrogate EndpointTestingThickThinnessTimeTrainingVisionVisual Fieldsanalytical methodarchetypal analysisclinical Diagnosisdata spacedesigndiagnostic accuracyearly onsetevidence baseexpectationfield studyhealth recordhigh dimensionalityimprovedintelligent algorithmmachine learning algorithmmultidimensional datanovelopen sourceoptical imagingoutcome forecastprogramsretinal ganglion cell degenerationretinal nerve fiber layertool
中文摘要
青光眼是一种复杂的神经退行性疾病,其导致视网膜神经节细胞变性,
它们的轴突随着老年人构成美国人口增长最快的一部分,青光眼将成为
在未来的几十年里,在美国将更加普遍。由于多种因素的复杂相互作用,
青光眼,需要更好的结构和功能预测其进展。的主要障碍
是大量的健康记录数据和复杂的计算模型。我们的总体目标是利用
大数据的力量和快速发展的机器学习方法。NEI的“从大数据到知识”
(BD 2K)”倡议和美国眼科学会视力智能研究(IRIS)注册
都是为了利用数据的力量,更好地了解疾病,
预防和治疗。
在这个多PI提案中,我们提供组装超过100万个光学相干断层扫描(OCT),
青光眼研究网络(GRN)的视野(VF)。我们建议开发一种混合人工
智能(AI)算法,该算法综合了高斯混合模型期望最大化(GEM)和
使用VF识别青光眼进展及其监测的原型机器学习方法,
视网膜神经纤维层(RNFL)厚度测量。我们将把这些工具公开提供给
视觉和眼科研究社区。
我们提出的研究可以提供青光眼预后的实质性改善,
潜在地提供了用于青光眼临床试验的OCT和联合VF/OCT替代终点。
英文摘要
Glaucoma is a complex neurodegenerative disease that results in degeneration of retinal ganglion cells and
their axons. With older people making up the fastest growing part of the US population, glaucoma will become
even more prevalent in the US in the coming decades. Due to the complex interaction of multiple factors in
glaucoma, better structural and functional predictors are needed for its progression. The main impediments
are massive health record data and sophisticated computational models. Our overall goal is to leverage the
power of big data and rapidly evolving machine learning approaches. The NEI's “Big Data to Knowledge
(BD2K)” initiative and the American Academy of Ophthalmology Intelligent Research in Sight (IRIS) registry
are all efforts to exploit the power of data and to better understand diseases and to provide improved
prevention and treatment.
In this multi-PI proposal, we offer to assemble over 1 million optical coherence tomography (OCT) and
visual fields (VFs) from the glaucoma research network (GRN). We propose to develop a hybrid artificial
intelligence (AI) algorithm that synthesizes Gaussian mixture model expectation maximization (GEM) and
archetypal machine learning approach to identify glaucoma progression and its monitoring using VFs and
retinal nerve fiber layer (RNFL) thickness measurements. We will make these tools openly available to the
vision and ophthalmology research communities.
Our proposed studies could offer substantial improvements in the prognosis of glaucoma as well as
potentially providing OCT and joint VF/OCT surrogate endpoints to be used in glaucoma clinical trials.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Promise of Optical Coherence Tomography Angiography in Determining Progression of Glaucoma.
光学相干断层扫描血管造影在确定青光眼进展方面的前景。
DOI:
10.1001/jamaophthalmol.2019.0467
发表时间:
2019
期刊:
JAMA ophthalmology
影响因子:
8.1
作者:
[Yousefi,Siamak]
通讯作者:
Yousefi,Siamak
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
-
批准号:10018038
-
项目类别:
-
资助金额:$47.34万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Associating retinal nerve fiber layer thickness with glucose metabolism and diabetic retinopathy
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批准号:10002287
-
项目类别:
-
资助金额:$24.03万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
-
批准号:10669671
-
项目类别:
-
资助金额:$46.12万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Associating retinal nerve fiber layer thickness with glucose metabolism and diabetic retinopathy
-
批准号:9809589
-
项目类别:
-
资助金额:$31.38万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
-
批准号:10245094
-
项目类别:
-
资助金额:$44.83万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
-
批准号:10454416
-
项目类别:
-
资助金额:$44.56万
-
财政年份:2019
-
负责人:Tobias Elze
-
依托单位:
Core Grant for Vision Research-LABORATORY COMPUTER APPLICATIONS MODULE (LCAM)
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批准号:10705719
-
项目类别:
-
资助金额:$20.36万
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财政年份:1997
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负责人:Tobias Elze
-
依托单位:
海外基金