Literature DB >> 30264216

Developing a More Responsive Radiology Resident Dashboard.

Hongyu Chen1, Vineeth Gangaram2, George Shih3.   

Abstract

Residents have a limited time to be trained. Although having a highly variable caseload should be beneficial for resident training, residents do not necessarily get a uniform distribution of cases. By developing a dashboard where residents and their attendings can track the procedures they have done and cases that they have seen, we hope to give residents a greater insight into their training and into where gaps in their training may be occurring. By taking advantage of modern advances in NLP techniques, we process medical records and generate statistics describing each resident's progress so far. We have built the system described and its life within the NYP ecosystem. By creating better tracking, we hope that caseloads can be shifted to better close any individual gaps in training. One of the educational pain points for radiology residency is the assignment of cases to match a well-balanced curriculum. By illuminating the historical cases of a resident, we can better assign future cases for a better educational experience.

Entities:  

Keywords:  Dashboards; Deep learning; Machine learning; Medical education; NLP; Web development

Year:  2019        PMID: 30264216      PMCID: PMC6382641          DOI: 10.1007/s10278-018-0123-6

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  7 in total

1.  Automated coding of diagnoses--three methods compared.

Authors:  P Franz; A Zaiss; S Schulz; U Hahn; R Klar
Journal:  Proc AMIA Symp       Date:  2000

2.  "Understanding" medical school curriculum content using KnowledgeMap.

Authors:  Joshua C Denny; Jeffrey D Smithers; Randolph A Miller; Anderson Spickard
Journal:  J Am Med Inform Assoc       Date:  2003-03-28       Impact factor: 4.497

3.  Automated encoding of clinical documents based on natural language processing.

Authors:  Carol Friedman; Lyudmila Shagina; Yves Lussier; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2004-06-07       Impact factor: 4.497

4.  Comparison of radiology residency programs in ten countries.

Authors:  J M G Willatt; A C Mason
Journal:  Eur Radiol       Date:  2005-02-09       Impact factor: 5.315

5.  Construction of a semi-automated ICD-10 coding help system to optimize medical and economic coding.

Authors:  Suzanne Pereira; Aurélie Névéol; Philippe Massari; Michel Joubert; Stefan Darmoni
Journal:  Stud Health Technol Inform       Date:  2006

6.  Workload of radiologists in United States in 2006-2007 and trends since 1991-1992.

Authors:  Mythreyi Bhargavan; Adam H Kaye; Howard P Forman; Jonathan H Sunshine
Journal:  Radiology       Date:  2009-06-09       Impact factor: 11.105

7.  Automatic construction of rule-based ICD-9-CM coding systems.

Authors:  Richárd Farkas; György Szarvas
Journal:  BMC Bioinformatics       Date:  2008-04-11       Impact factor: 3.169

  7 in total
  2 in total

Review 1.  Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review.

Authors:  Kai Siang Chan; Nabil Zary
Journal:  JMIR Med Educ       Date:  2019-06-15

2.  Developing a dashboard to meet the needs of residents in a competency-based training program: A design-based research project.

Authors:  Robert Carey; Grayson Wilson; Venkat Bandi; Debajyoti Mondal; Lynsey J Martin; Rob Woods; Teresa Chan; Brent Thoma
Journal:  Can Med Educ J       Date:  2020-12-07
  2 in total

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