增长的数据科学 在非洲促进进步的研究 (GRASP) 计划:理由和概述
Ezinne Uvere1,2, Judit Kumuthini3, Segun Fatumo4
1Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria.
概括
非洲不断增长的数据科学研究以刺激进步 (GRASP) 计划建立了非洲的数据科学研究能力. 它旨在促进大脑健康和非传染性疾病 (NCD) 的创新解决方案.
科学领域:
- 神经科学与公共卫生
- 数据科学在健康研究研究中的数据科学
- 在非洲的研究能力建设.
背景情况:
- 大脑健康对整体福祉和实现可持续发展目标至关重要.
- 非洲面临着大脑健康研究专业培训的缺陷,特别是在遗传,社会人口和生活方式因素方面.
- 需要在非洲学者中建立可持续的数据科学研究能力.
研究的目的:
- 在非洲建立增长的数据科学研究以刺激进步 (GRASP) 计划.
- 增强数据科学技能,探索大脑健康决定因素,包括社会人口统计,饮食,生活方式,认知,基因组,气候和地理数据.
- 促进非洲大脑健康和打击非传染性疾病 (NCD) 的创新解决方案.
主要方法:
- 一个为期三年的计划,整合了虚拟培训,伊巴丹大学的住院,网络和指导.
- 从一个多学科的研究生池中选择了十名非洲学者.
- 专注于提高数据科学技能,以分析复杂的健康决定因素和心血管风险.
主要成果:
- 十名学者被选为2024年周期,接受一个为期九个月的研究生证书课程.
- 优秀的学者参加了为期6周的实习,在毕业后3年内进行持续评估.
- 该计划旨在为创新的大脑健康解决方案建立一个可持续的系统.
结论:
- 格拉斯普计划旨在在非洲建立可持续的数据科学研究能力.
- 它旨在激发创新思维,为大脑健康和非传染性疾病创造变革性的解决方案.
- 数据科学研究能力建设将重新定位对非洲抗击非传染性疾病的理解和方法.
相关概念视频
Statgraphics
196
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
196
Statistical Analysis System (SAS)
359
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
359
Genome-wide Association Studies-GWAS
14.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
14.3K
Statistical Analysis: Overview
7.4K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
7.4K
Introduction to R
621
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
621


