Artificial Intelligence in Modelling the Influence of Socio-Economic Factors on the Risk of Cardiovascular Events

人工智能模拟社会经济因素对心血管事件风险的影响

• 批准号: 2609865
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2609865
• 关键词: Artificial; Intelligence; Modelling; Influence; Socio

Studentship strategic priority area: Mathematics, Statistics and ComputationKeywords: Cardiovascular Disease, Artificial Intelligence Cardiovascular diseases (CVDs) are leading cause of morbidity and mortality worldwide, especially in older people, despite substantial advances in diagnosis and treatment. Application of artificial intelligence (AI) offers state-of-the-art data modelling and interpretation to inform and support clinical decisions. AI techniques such as machine learning and deep learning can improve medical knowledge, by providing advanced insights into healthcare choices based on longitudinal health records. The emerging multidisciplinary field of healthcare and AI will become increasingly important in informing people and healthcare professionals about how medical events and decisions are associated with and potential influence outcome. However, medical events may be strongly influenced by affluence and social deprivation. My research will use NHS administrative data from Greater Glasgow & Clyde Health Board for adults age >50 years (the age at which the incidence and prevalence of disease affecting older people increases rapidly). This comprises a large dataset including demographics, blood tests, electrocardiograms and echocardiograms, primary-care prescriptions, hospitalisations and procedures and mortality. For a large subset, additional primary care data on smoking, blood pressure and body mass index can be obtained. I will use these data to explore the common sequence of events (e.g. smoking, hypertension and obesity, leading to diabetes, renal dysfunction and atherosclerosis and onwards to myocardial infarction, heart failure, stroke, disability and death) and accounting for age, their relationship to affluence and social deprivation.

学生奖学金战略优先领域：数学，统计和计算关键词：心血管疾病，人工智能心血管疾病（CVD）是全球发病率和死亡率的主要原因，特别是在老年人中，尽管诊断和治疗取得了重大进展。人工智能（AI）的应用提供了最先进的数据建模和解释，为临床决策提供信息和支持。机器学习和深度学习等人工智能技术可以通过提供基于纵向健康记录的医疗保健选择的先进见解来改善医疗知识。新兴的医疗保健和人工智能多学科领域将在告知人们和医疗保健专业人员医疗事件和决策如何与潜在影响结果相关方面变得越来越重要。然而，医疗事件可能受到富裕和社会剥夺的强烈影响。我的研究将使用来自大格拉斯哥和克莱德卫生委员会的NHS管理数据，用于年龄>50岁的成年人（影响老年人的疾病发病率和患病率迅速增加的年龄）。这包括一个大型数据集，包括人口统计学，血液测试，心电图和超声心动图，初级保健处方，住院和手术以及死亡率。对于一个大的子集，可以获得有关吸烟、血压和体重指数的额外初级保健数据。我将使用这些数据来探索事件的常见顺序（例如，吸烟，高血压和肥胖，导致糖尿病，肾功能不全和动脉粥样硬化，进而导致心肌梗死，心力衰竭，中风，残疾和死亡），并解释年龄，它们与富裕和社会剥夺的关系。