Literature DB >> 34075769

Pathology Informatics Education during the COVID-19 Pandemic at Memorial Sloan Kettering Cancer Center (MSKCC).

David Kim1, Matthew G Hanna2, Chad Vanderbilt2, S Joseph Sirintrapun2.   

Abstract

This review details the development and structure of a four-week rotation in pathology informatics for a resident trainee at Memorial Sloan Kettering Cancer Center (MSKCC) in New York City so that other programs interested in such a rotation can refer to. The role of pathology informatics is exponentially increasing in research and clinical practice. With an ever-expanding role, training in pathology informatics is paramount as pathology training programs and training accreditation bodies recognize the need for pathology informatics in training future pathologists. However, due to its novelty, many training programs are unfamiliar with implementing pathology informatics training. The rotation incorporates educational resources for pathology informatics, guidance in the development, and general topics relevant to pathology informatics training. Informatics topics include anatomic pathology related aspects such as whole slide imaging, laboratory information systems, image analysis, and molecular pathology associated issues such as the bioinformatics pipeline and data processing. Additionally, we highlight how the rotation pivoted to meet the department's informatics needs while still providing an educational experience during the onset of the COVID-19 pandemic.
CONCLUSION: As pathology informatics continues to grow and integrate itself into practice, informatics education must also grow to meet the future needs of pathology. As informatics programs develop across institutions, such as the one detailed in this paper, these programs will better equip future pathologists with informatics to approach disease and pathology.
Copyright © 2021 by Academy of Sciences and Arts of Bosnia and Herzegovina.

Entities:  

Keywords:  Digital Pathology; Informatics Education; Molecular and Genomic Pathology Education; Residency; Whole Slide Imaging

Mesh:

Year:  2021        PMID: 34075769     DOI: 10.5644/ama2006-124.331

Source DB:  PubMed          Journal:  Acta Med Acad        ISSN: 1840-1848


  1 in total

1.  Preoperative prediction of pelvic lymph nodes metastasis in prostate cancer using an ADC-based radiomics model: comparison with clinical nomograms and PI-RADS assessment.

Authors:  Xiang Liu; Xiangpeng Wang; Yaofeng Zhang; Zhaonan Sun; Xiaodong Zhang; Xiaoying Wang
Journal:  Abdom Radiol (NY)       Date:  2022-06-28
  1 in total

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