【レポートの概要(一部)】
1 Table of Contents
1 Table of Contents 4
1.1 List of Tables 5
1.2 List of Figures 7
2 Introduction 8
2.1 Catalyst 8
2.2 Upcoming Reports 9
3 Epidemiology 10
3.1 Disease Background 10
3.2 Risk Factors and Comorbidities 10
3.3 Global Trends 11
3.3.1 US 12
3.3.2 5EU 12
3.3.3 Japan 13
3.4 Forecast Methodology 13
3.4.1 Sources Used 15
3.4.2 Sources Not Used 17
3.4.3 Forecast Assumptions and Methods — Diagnosed Prevalent Cases of Diabetes 18
3.4.4 Forecast Assumptions and Methods — Diagnosed Prevalent Cases of Diabetic Retinopathy 21
3.4.5 Forecast Assumptions and Methods – Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population 22
3.4.6 Forecast Assumptions and Methods – Total Prevalent Cases of ME following BRVO and CRVO 23
3.5 Epidemiological Forecast for Macular Edema (2013-2023) 25
3.5.1 Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population 25
3.5.2 Age-Specific Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population 27
3.5.3 Sex-Specific Diagnosed Prevalent Cases of DME in the Diagnosed Diabetic Retinopathy Population 29
3.5.4 Total Prevalent Cases of ME following BRVO 31
3.5.5 Age-Specific Total Prevalent Cases of ME following BRVO 33
3.5.6 Sex-Specific Total Prevalent Cases of ME following BRVO 35
3.5.7 Total Prevalent Cases of ME following CRVO 37
3.5.8 Age-Specific Total Prevalent Cases of ME following CRVO 39
3.5.9 Sex-Specific Total Prevalent Cases of ME following CRVO 41
3.6 Discussion 43
3.6.1 Epidemiological Forecast Insight 43
3.6.2 Limitations of the Analysis 44
3.6.3 Strengths of the Analysis 45
4 Appendix 46
4.1 Bibliography 46
4.2 About the Authors 50
4.2.1 Epidemiologists 50
4.2.2 Reviewers 50
4.2.3 Acting Director of Epidemiology 52
4.2.4 Global Head of Healthcare 52
4.3 About GlobalData 53
4.4 About EpiCast 53
4.5 Disclaimer 54
【レポート販売概要】
■ タイトル:糖尿病黄斑浮腫:疫学的予測(~2023)■ 英文:EpiCast Report: Diabetic Macular Edema - Epidemiology Forecast to 2023
■ 発行日:2014年9月10日
■ 調査会社:GlobalData
■ 商品コード:GDHCER031-14
■ 調査対象地域:グローバル
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- グラフデータベースの世界市場:コンポーネント別(ソフトウェア、サービス)、展開モデル別(オンプレミス、クラウド)、データベースタイプ別(リレーショナル(SQL)、非リレーショナル(NoSQL))、分析タイプ別(パス分析、接続性分析、コミュニティ分析、中心性分析)、用途別(不正検出およびリスク管理、マスターデータ管理、顧客分析、IDおよびアクセス管理、推奨エンジン、プライバシーおよびリスクコンプライアンス、その他)A graph database is an online database management system where connected elements are linked together. It is an ideal solution to store data and to connect relationships between the data much more accurately than a relational database (RDBMS). A graph database is gathering of nodes and edges where every node represents a substance, for example, a person or business and each edge represents a conne …
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