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Moving to a data informed understanding of cerebrovascular small vessel disease.

Moving to a data informed understanding of cerebrovascular small vessel disease.
通过数据了解脑血管小血管疾病。
批准号:
2765783
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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英文摘要
Studentship strategic priority area: E-Health Informatics ResearchKeywords: Big data, cerebrovascular, phenome wide association study, small vessel disease The syndrome of cerebral small vessel disease (cSVD) is arguably one of the most important conditions of our time, contributing to stroke, dementia, and other age-related problems. Despite the importance of cSVD, our understanding of the condition remains limited.This project will explore the physical, psychological, and other manifestations of cSVD, offering new insights into the disease phenotype that will improve assessment, inform diagnosis and shape future research trials.The project will work with large data registries including UK Biobank and Dementia Platforms UK. A primary aim will be to complete a phenome wide association study describing the clinical features seen in people with neuroimaging evidence of small vessel disease. Results will be validated in independent cohorts and placed in the context of existing research. For this PhD, we have designed a program of complementary, interlinked, projects each designed to equip the student with a different research skill and spanning key areas such as neuroimaging, 'big data', evidence synthesis and communication of science. At completion, the student will be equipped with the skills needed to become an independent researcher. The program also provides an opportunity for the student to further develop their knowledge and skills in a particular focused area of their choice, for example neuroimaging or analytics.
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: