Data Science Applications in Communication andSwallowing Disorders

数据科学在沟通和吞咽障碍中的应用

基本信息

批准号：
10322652
负责人：
BONNIE J MARTIN-HARRIS
金额：
$ 18.32万
依托单位：
NORTHWESTERN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10322652
关键词：
Algorithms Area Award Barium swallow Big Data Big Data Methods Bioinformatics Biological Biomedical Research Biometry Chronic Obstructive Pulmonary Disease Classification Clinical Communication Communication impairment Computer Vision Systems Computerized Medical Record Computers Data Data Analyses Data Science Data Scientist Data Set Deglutition Deglutition Disorders Dementia Development Diagnosis Disease Economics Electronic Health Record Engineering Explosion Funding Geography Goals Grant Head and Neck Cancer Health Hearing Impairment Individual Instruction Intervention Laboratories Machine Learning Medical Medical Records Mentored Patient-Oriented Research Career Development Award Mentors Mentorship Methods Mid-Career Clinical Scientist Award (K24)Mission Modernization National Institute on Deafness and Other Communication Disorders Nutritional Outcome Parkinson Disease Patient Care Patient Care Planning Patients Pattern Phenotype Physiological Productivity Publishing Registries Reproducibility Research Research Personnel Research Project Grants Sample Size Science Scientific Inquiry Scientist Secure Severities Speech Standardization Statistical Models Strategic Planning Stroke Supervision Techniques Testing Training United States National Institutes of Health Work base career career development clinical practice clinically relevant computer science computerized data registry data resource data warehouse digital experimental study health assessment high risk human error impression improved improved outcome learning algorithm novel patient oriented programs research and development skills statistical learning theories uptake

项目摘要

PROJECT SUMMARY/ABSTRACT The emergence of electronic medical records, large data registries and readily accessible, protected servers have resulted in an explosion of digital information with potentially high clinical impact for improving patient management and outcomes. Big data warehouses that capture standardized information within the scope of clinical practices allow trained scientists to not only engage in traditional hypothesis testing, but to also uncover new hypotheses, refine existing theories and apply new discoveries to health assessments and interventions. Despite the accessibility and potential impact of these data platforms, clinician scientists have traditionally directed experiments that incorporate relatively small sample sizes and data from individual laboratories, and have not been trained in big data analytics or in engaging appropriate team scientists who work in this space, such as computer scientists, biostatisticians and engineers. The overarching goal of this proposal is to mentor early patient oriented communication and swallowing scientists in big data analytics and to mentor and involve early data science scholars in communication and swallowing research. The PI proposes four primary mentorship and research goals in this K24 renewal proposal: 1. Train a cadre of early stage communication and swallowing scientists in data science methods, including machine learning, by an expert, interdisciplinary, collaborative data science team, 2. Engage and introduce early career data scientists from fields of biostatistics, computer science and engineering to communication and swallowing sciences, and respective data sets, toward facilitating interdisciplinary data science teams and research productivity, 3. Apply novel data science methods to identify phenotypes of swallowing impairment and severity classifications in patient groups known to be at high risk for nutritional and health complications related to dysphagia, and 4. Develop a new area of research in machine learning applications toward improving reliability of physiologic swallowing assessment. The data science theme of the career development and research plan directly align with NIDCD's Strategic Plan for Data Science which lists as its mission: Storing, managing, standardizing and publishing the vast amounts of data produced by biomedical research. NIDCD recognizes that accessible, well-organized, secure and efficiently operated data resources are critical to modern scientific inquiry…and by maximizing the value of data generated through NIH-funded efforts, the pace of biomedical discoveries and medical breakthroughs for better health outcomes can be accelerated.

项目概要/摘要电子病历、大数据登记和易于访问、受保护的服务器的出现已经导致了数字信息的爆炸式增长，对改善患者的病情具有潜在的巨大临床影响管理和结果捕获标准化信息的大数据仓库。临床实践使训练有素的科学家不仅可以进行传统的假设检验，还可以发现新假设，完善现有理论并将新发现应用于健康评估和尽管这些数据平台具有可访问性和潜在影响，但临床科学家已经传统的定向实验包含相对较小的样本量和来自个体的数据实验室，并且没有接受过大数据分析培训或聘请适当的团队科学家，这些科学家在这个领域工作的人，例如计算机科学家、生物统计学家和工程师。该提案旨在指导早期以患者为导向的沟通和吞咽科学家的大数据分析和指导并让早期数据科学学者参与交流和吞咽研究。 K24更新提案的四个主要指导和研究目标： 1. 培养早期骨干人员由专家通过数据科学方法（包括机器学习）与科学家进行沟通和吞咽，跨学科、协作的数据科学团队，2. 聘请并引入来自以下国家的早期职业数据科学家：生物统计学、计算机科学和工程、通信和吞咽科学领域，以及各自的数据集，以促进跨学科数据科学团队和研究生产力，3.应用新的数据科学方法来识别吞咽障碍的表型和严重程度分类已知处于吞咽困难相关营养和健康并发症高风险的患者群体，以及 4. 开发机器学习应用的新研究领域，以提高生理学的可靠性吞咽评估的职业发展和研究计划的数据科学主题直接吻合。 NIDCD 的数据科学战略计划将其使命列为：存储、管理、标准化和 NIDCD 发布生物医学研究产生的大量数据，认识到这些数据是可获取的、可获取的。组织良好、安全且高效运行的数据资源对于现代科学探究至关重要……并且通过最大化 NIH 资助的工作产生的数据的价值，生物医学发现的步伐可以加速实现更好健康结果的医学突破。