Biomedical Data Science Graduate Training at Stanford

斯坦福大学生物医学数据科学研究生培训

• 批准号: 9901621
• 负责人: SYLVIA KATINA PLEVRITIS
• 金额: $ 30.84万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9901621
• 关键词: Training; biomedical data science

 DESCRIPTION (provided by applicant): The expanded ability to collect data at all scales-molecular, cellular, tissue, organism and population-has created unparalleled opportunities for biomedical discovery. These opportunities cross all areas of research from basic science to clinical care. In response to these tremendously exciting emerging challenges in data science, Stanford University announced the creation of a new Department of Biomedical Data Science (DBDS) to begin in fall of 2015. Fundamental to the DBDS is bringing together faculty in (1) informatics and computer science, and (2) biostatistics and mathematical modeling, who work closely with a broad range of (3) biomedical science collaborators to advance knowledge. The Stanford Biomedical Informatics (BMI) training program is focused on the creation of new methods for the organization, analysis and modeling of biomedical data and knowledge. The BMI program has been a small interdisciplinary program at Stanford for more than 33 years; nonetheless, it has produced many leaders in biomedical informatics and data science. The BMI program will now have its administrative home in the DBDS, and will become the epicenter for biomedical data science training at Stanford. We are able quickly to respond to the shortage of trained scientists in biomedical data science because of a flexible curriculum, an unusually fertile set of course offerings, and a plethora of research opportunities. In this proposal, we outline a plan to engage faculty broadly across the University to create scalable mechanisms for training the next generation of biomedical data scientists, and creating a pathway for "data science" within the BMI program that stresses statistical reasoning, machine learning and data mining of biomedical data.

 描述（由申请人提供）：收集所有尺度（分子、细胞、组织、有机体和群体）数据的能力的扩展为生物医学发现创造了无与伦比的机会，这些机会涵盖从基础科学到临床护理的所有研究领域。为了应对数据科学领域这些令人兴奋的新兴挑战，斯坦福大学宣布于 2015 年秋季开始创建新的生物医学数据科学系 (DBDS)。DBDS 的基础是将以下领域的教师聚集在一起： (1) 信息学和计算机科学，以及 (2) 生物统计学和数学建模，他们与广泛的 (3) 生物医学科学合作者密切合作，以推进知识的发展。斯坦福大学生物医学信息学 (BMI) 培训计划的重点是创建生物医学数据和知识的组织、分析和建模的新方法 BMI 项目作为斯坦福大学的一个小型跨学科项目已有超过 33 年的历史；尽管如此，它还是培养了许多生物医学信息学和数据科学领域的领导者。现在，其行政中心将设在 DBDS，并将成为斯坦福大学生物医学数据科学培训的中心，由于灵活的课程和异常丰富的人才库，我们能够快速应对生物医学数据科学领域受过训练的科学家的短缺。在这份提案中，我们概述了一项计划，让整个大学的教师广泛参与，创建可扩展的机制来培训下一代生物医学数据科学家，并在该领域内创建“数据科学”的途径。 BMI 计划强调生物医学数据的统计推理、机器学习和数据挖掘。

项目成果

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data

语言模型是电子健康记录数据的有效患者表示学习技术

• 发表时间: 2020-01-06
• 期刊: ArXiv
• 作者: E. Steinberg;Kenneth Jung;Jason Alan Fries;Conor K. Corbin;S. Pfohl;N. Shah
• 通讯作者: N. Shah

Coalitional Game Theory Facilitates Identification of Non-Coding Variants Associated With Autism.

联盟博弈论有助于识别与自闭症相关的非编码变异。

• 发表时间: 2019
• 作者: Sun, Min Woo;Gupta, Anika;Varma, Maya;Paskov, Kelley M;Jung, Jae;Stockham, Nate T;Wall, Dennis P
• 通讯作者: Wall, Dennis P

Ontology-driven weak supervision for clinical entity classification in electronic health records.

本体驱动的电子健康记录中临床实体分类的弱监督。

• 发表时间: 2020-08-05
• 作者: Fries, Jason A;Steinberg, Ethan;Khattar, Saelig;Fleming, Scott L;Posada, Jose;Callahan, Alison;Shah, Nigam H
• 通讯作者: Shah, Nigam H

Assessing the accuracy of automatic speech recognition for psychotherapy.

评估心理治疗自动语音识别的准确性。

• 发表时间: 2020
• 作者: Miner, Adam S;Haque, Albert;Fries, Jason A;Fleming, Scott L;Wilfley, Denise E;Terence Wilson, G;Milstein, Arnold;Jurafsky, Dan;Arnow, Bruce A;Stewart Agras, W;Fei;Shah, Nigam H
• 通讯作者: Shah, Nigam H

Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network.

在 OHDSI 网络中开发和验证大规模预测急性缺血性卒中症状出血性转化的预后模型。

• 发表时间: 2020
• 影响因子: 3.7
• 作者: Wang, Qiong;Reps, Jenna M;Kostka, Kristin Feeney;Ryan, Patrick B;Zou, Yuhui;Voss, Erica A;Rijnbeek, Peter R;Chen, RuiJun;Rao, Gowtham A;Morgan Stewart, Henry;Williams, Andrew E;Williams, Ross D;Van Zandt, Mui;Falconer, Thomas;Fernandez
• 通讯作者: Fernandez