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英文摘要
Since 1998, the Pittsburgh Biomedical Informatics Training Program (BMITP) has provided advanced training in the application of computing to challenging problems in biomedicine. In addition to our long history, our program is notable for continuous evolution of our programs, a highly collaborative research environment, and strong institutional support from the University of Pittsburgh and the University of Pittsburgh Medical Center (UPMC). BMITP is housed in the Department of Biomedical Informatics (DBMI) in Pitt’s School of Medicine. DBMI provides, space, equipment, and financial support for training program administration, faculty, and trainees. BMITP’s core faculty of 39 members, including the 19 faculty members with primary appointments in DBMI. BMITP is led by the Program Director and Associate Director, with the help of an experienced program administrator and a leadership group of faculty co-directors. The Pittsburgh Biomedical Informatics Training Program offers research training in translational bioinformatics, health care/clinical informatics, imaging informatics, clinical research informatics, and public health informatics. Trainees seek MS or PhD degrees in either Biomedical Informatics or through the Biomedical Informatics Track of the Intelligent Systems Program, housed in Pitt’s School of Computing and Information. We also train MD/PhD students through the University of Pittsburgh’s Medical Scientist Training Program. Postdoctoral trainees undertake advanced research, with the goal of developing research programs and funding applications that will support their transition to independence. A broad variety of courses at both the University of Pittsburgh and Carnegie-Mellon University are available to all trainees. During the past five years, we have revised our curriculum, our admissions processes, and our preliminary and comprehensive exams. We have also expanded our data science offerings and increased our outreach efforts with minority serving institutions. Our plans for the next five years include further strengthening of our evaluation efforts and our efforts to recruit diverse trainees, to enhance mentoring, to expand the range of internship opportunities available to trainees, and to use our streamlined evaluations to help trainees productively reach milestones and complete their degrees in a timely manner. We have a strong track record of training successful biomedical informatics researchers, many of whom have gone on to be leaders in the field. Trainees in our programs publish research articles in high-impact journals, win national awards for their research, successfully compete for NIH funding, and secure research positions in academia, industry, and government.
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DOI: 10.1371/journal.pone.0018657
发表时间: 2011
期刊: PloS one
影响因子: 3.7
作者: [Piwowar HA]
通讯作者: Piwowar HA
DOI: 10.3928/01484834-20211202-01
发表时间: 2022-01
期刊: The Journal of nursing education
影响因子: --
作者: [Rosa WE, Hartley K, Hassmiller SB, Frisch SO, Bennett SG, Breen K, Goldberg JI, Koschmann KS, Missel AL, de Campos AP, Pho AT, Rausch J, Schlak AE, Shook A, Tierney MK, Umberfield E, Fairman JA]
通讯作者: Fairman JA
DOI: 10.1186/s12864-017-3494-z
发表时间: 2017-03-14
期刊: BMC genomics
影响因子: 4.4
作者: [Chen V, Paisley J, Lu X]
通讯作者: Lu X
Detecting adverse drug events in discharge summaries using variations on the simple Bayes model.
使用简单贝叶斯模型的变体检测出院总结中的药物不良事件。
DOI: --
发表时间: 2003
期刊: AMIA ... Annual Symposium proceedings. AMIA Symposium
影响因子: --
作者: [Visweswaran,Shyam, Hanbury,Paul, Saul,Melissa, Cooper,GregoryF]
通讯作者: Cooper,GregoryF
175
    Cancer Deep Phenotyping from Electronic Medical Records
    • 批准号:
      10594128
    • 项目类别:
    • 资助金额:
      $18.86万
    • 财政年份:
      2022
    • 负责人:
      HARRY S HOCHHEISER
    • 依托单位:
    Cancer Deep Phenotype Extraction from Electronic Medical Records
    • 批准号:
      10058470
    • 项目类别:
    • 资助金额:
      $92.47万
    • 财政年份:
      2020
    • 负责人:
      HARRY S HOCHHEISER
    • 依托单位:
    Cancer Deep Phenotype Extraction from Electronic Medical Records
    • 批准号:
      10268998
    • 项目类别:
    • 资助金额:
      $85.92万
    • 财政年份:
      2020
    • 负责人:
      HARRY S HOCHHEISER
    • 依托单位:
    Cancer Deep Phenotype Extraction from Electronic Medical Records
    • 批准号:
      10472741
    • 项目类别:
    • 资助金额:
      $83.88万
    • 财政年份:
      2020
    • 负责人:
      HARRY S HOCHHEISER
    • 依托单位:
    海外基金