Culturally Augmented Learning In Biomedical Informatics Research (CALIBIR) Program

生物医学信息学研究中的文化增强学习 (CALIBIR) 计划

基本信息

项目摘要

PROJECT SUMMARY/ABSTRACT The Culturally Augmented Learning In Biomedical Informatics Research (CALIBIR) program will address the clear need to enhance diversity within the biomedical informatics and data science field, particularly the dearth of underrepresented individuals pursuing graduate programs and careers in different areas of this field. The CALIBIR program builds on the research strengths in biomedical informatics and data science and the existing didactic training in biomedical informatics, engineering, statistics, and computer science topics at Wake Forest School of Medicine and Wake Forest University. The Program Faculty (including the Program Directors) have vast academic and professional experiences; a history of administration and collaboration on diversity-focused research and training programs; and ongoing research and funding in the five research domains proposed for CALIBIR training: Clinical Research Informatics, Artificial Intelligence, Healthcare Informatics, Imaging Informatics, and Translational Bioinformatics. Thus, we are well-positioned to offer a 10-week summer research immersion experience to train and educate undergraduate and master’s level underrepresented students and promote greater interest, exposure, and research experiences in biomedical informatics and data science. The CALIBIR program will support mentored research training activities of 60 scholars (12 students per summer). The program's overall goals are to: 1) increase underrepresented students' skills, preparation, and commitment to participate in cutting-edge biomedical informatics research; 2) offer lectures and hands-on demonstrations on state-of-the-art biomedical informatics techniques via a “Biomedical Informatics Boot Camp”; 3) provide group seminars and networking events covering responsible conduct of research, scientific dissemination, and professional development topics; 4) build trainee experience in scientific communication via a journal club, writing workshop, and an abstract and oral presentation of their research; 5) cultivate influential and long-lasting collaborative relationships between trainees and mentors to highlight the value of teamwork in research and provide an accepting and inclusive environment that will positively impact students from diverse backgrounds; and 6) encourage underrepresented students to pursue doctoral studies and careers in biomedical informatics and data science fields through an experience that exemplifies the excitement and challenges of clinically relevant investigations. The overarching goal of the CALIBIR program is to expand the pool of underrepresented students who successfully complete a graduate degree in a biomedical informatics- related field up to a PhD and increase the diversity of the biomedical informatics and data science workforce. In sum, the CALIBIR program takes advantage of unique strengths, existing infrastructure, and long-standing collaborations among diverse program faculty to ensure the successful creation and implementation of the program. It offers several innovative approaches to provide both technical and professional preparation to recruit and retain underrepresented students in the biomedical informatics and data science fields.
项目总结/文摘

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Metin Nafi Gurcan其他文献

Gene pointNet for tumor classification
  • DOI:
    10.1007/s00521-024-10307-x
  • 发表时间:
    2024-08-22
  • 期刊:
  • 影响因子:
    4.500
  • 作者:
    Hao Lu;Mostafa Rezapour;Haseebullah Baha;Muhammad Khalid Khan Niazi;Aarthi Narayanan;Metin Nafi Gurcan
  • 通讯作者:
    Metin Nafi Gurcan
Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning
  • DOI:
    10.1186/s12864-025-11553-6
  • 发表时间:
    2025-04-10
  • 期刊:
  • 影响因子:
    3.700
  • 作者:
    Mostafa Rezapour;Aarthi Narayanan;Wyatt H. Mowery;Metin Nafi Gurcan
  • 通讯作者:
    Metin Nafi Gurcan

Metin Nafi Gurcan的其他文献

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{{ truncateString('Metin Nafi Gurcan', 18)}}的其他基金

Computer-assisted diagnosis of ear pathologies by combining digital otoscopy with complementary data using machine learning
通过使用机器学习将数字耳镜与补充数据相结合来计算机辅助诊断耳部病变
  • 批准号:
    10564534
  • 财政年份:
    2023
  • 资助金额:
    $ 13.5万
  • 项目类别:
Efficient and cost-effective breast cancer risk stratification using whole slide histopathology images
使用全玻片组织病理学图像进行高效且经济的乳腺癌风险分层
  • 批准号:
    10649978
  • 财政年份:
    2023
  • 资助金额:
    $ 13.5万
  • 项目类别:
Analytics & Machine-learning for Maternal-health Interventions (AMMI): A Cross-CTSA Collaboration
分析
  • 批准号:
    10670448
  • 财政年份:
    2022
  • 资助金额:
    $ 13.5万
  • 项目类别:
Culturally Augmented Learning In Biomedical Informatics Research (CALIBIR) Program
生物医学信息学研究中的文化增强学习 (CALIBIR) 计划
  • 批准号:
    10701848
  • 财政年份:
    2022
  • 资助金额:
    $ 13.5万
  • 项目类别:
Auto-Scope Software-Automated Otoscopy to Diagnose Ear Pathology
Auto-Scope 软件 - 用于诊断耳部病理的自动耳镜检查
  • 批准号:
    9790958
  • 财政年份:
    2018
  • 资助金额:
    $ 13.5万
  • 项目类别:
Pathology Image Informatics Platform for visualization, analysis and management
用于可视化、分析和管理的病理图像信息学平台
  • 批准号:
    9341177
  • 财政年份:
    2015
  • 资助金额:
    $ 13.5万
  • 项目类别:
Computer-assisted Grading and Risk Stratification of Follicular Lymphoma
滤泡性淋巴瘤的计算机辅助分级和风险分层
  • 批准号:
    8215904
  • 财政年份:
    2009
  • 资助金额:
    $ 13.5万
  • 项目类别:
Computer-based assessment of tumor microenvironment (TME) in Follicular Lymphoma
基于计算机的滤泡性淋巴瘤肿瘤微环境 (TME) 评估
  • 批准号:
    9611415
  • 财政年份:
    2009
  • 资助金额:
    $ 13.5万
  • 项目类别:
OAMiner: Integrative Knowledge Anchored Hypothesis Discovery
OMiner:综合知识锚定假设发现
  • 批准号:
    7828221
  • 财政年份:
    2009
  • 资助金额:
    $ 13.5万
  • 项目类别:
Computer-assisted Grading and Risk Stratification of Follicular Lymphoma
滤泡性淋巴瘤的计算机辅助分级和风险分层
  • 批准号:
    8024533
  • 财政年份:
    2009
  • 资助金额:
    $ 13.5万
  • 项目类别:

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