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Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)


useR! 2020: Report generation in clinical trials using R and knitr (A. Maggiorelli), lightning.
useR! 2020: Mortality Minder (K. Bhanot), regular.
useR! 2020: pepFunk: enrichment for metaproteomic gut microbiome data (C. Simopoulos), regular.
useR! 2020: Building descriptive tables with the updated compareGroups package (I. Subirana), poster.
useR! 2020: Rejustify AI-enhanced ETL engine (M. Wolski), regular.
useR! 2020: MUACz: Generating MUAC and BMI z-scores and Percentiles (L. Mramba), poster.
useR! 2020: Comparing the Treatment Regimen of Pediatric Leukemia Patients (S. Davis), poster.
useR! 2020: MeningiOMICS (K. O'Shea), lightning.
useR! 2020: Robust alternatives for comparing time-event survival curves (L. Stepanek), lightning.


We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
This course will provide participants with the skills and knowledge to generate reports in clinical trials using R and knitr, create descriptive tables with the updated compareGroups package, develop an AI-enhanced ETL engine, generate MUAC and BMI z-scores and Percentiles, compare the treatment regimen of pediatric leukemia patients, and analyze meningiOMICS data. Additionally, participants will learn robust alternatives for comparing time-event survival curves.

How does this course contribute to professional growth?
This course provides a comprehensive overview of the use of R and knitr for report generation in clinical trials, as well as a variety of other topics related to biostatistics. It offers a unique opportunity to learn from experts in the field, and to gain hands-on experience with the latest tools and techniques. By attending this course, professionals can gain valuable insights into the latest developments in biostatistics, and can develop their skills in data analysis, visualization, and report generation. This course can also help professionals stay up-to-date with the latest trends in the field, and can provide them with the knowledge and skills necessary to stay competitive in the job market.

Is this course suitable for preparing further education?
This course appears to be suitable for preparing further education, as it covers a wide range of topics related to biostatistics and data analysis. The course includes topics such as report generation in clinical trials, mortality minder, enrichment for metaproteomic gut microbiome data, building descriptive tables, AI-enhanced ETL engine, generating MUAC and BMI z-scores and percentiles, comparing the treatment regimen of pediatric leukemia patients, MeningiOMICS, and robust alternatives for comparing time-event survival curves. All of these topics are relevant to biostatistics and data analysis, and could be useful for further education.