<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>vikrant31.r-universe.dev</title><link>https://vikrant31.r-universe.dev</link><description>Recent package updates in vikrant31</description><generator>R-universe</generator><image><url>https://github.com/vikrant31.png</url><title>R packages by vikrant31</title><link>https://vikrant31.r-universe.dev</link></image><lastBuildDate>Mon, 11 May 2026 08:53:15 GMT</lastBuildDate><item><title>[vikrant31] HCUPtools 1.0.1</title><author>rathore.vikrant@gmail.com (Vikrant Dev Rathore)</author><description>A comprehensive R package for accessing and working with
publicly available and free resources from the Agency for
Healthcare Research and Quality (AHRQ) Healthcare Cost and
Utilization Project (HCUP). The package provides streamlined
access to HCUP's Clinical Classifications Software Refined
(CCSR) mapping files and Summary Trend Tables, enabling
researchers and analysts to efficiently map ICD-10-CM diagnosis
codes and ICD-10-PCS procedure codes to CCSR categories and
access HCUP statistical reports. Key features include: direct
download from HCUP website, multiple output formats
(long/wide/default), cross-classification support, version
management, citation generation, and intelligent caching. The
package does not redistribute HCUP data files but facilitates
direct download from the official HCUP website, ensuring users
always have access to the latest versions and maintain
compliance with HCUP data use policies. This package only
accesses free public tools and reports; it does NOT access HCUP
databases (NIS, KID, SID, NEDS, etc.) that require purchase.
For more information, see &lt;https://hcup-us.ahrq.gov/&gt;.</description><link>https://github.com/r-universe/vikrant31/actions/runs/27257356110</link><pubDate>Mon, 11 May 2026 08:53:15 GMT</pubDate><r:package>HCUPtools</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://vikrant31.r-universe.dev</r:repository><r:upstream>https://github.com/vikrant31/hcuptools</r:upstream><r:article><r:source>HCUPtools.Rmd</r:source><r:filename>HCUPtools.html</r:filename><r:title>Getting Started with HCUPtools</r:title><r:created>2025-11-30 08:08:17</r:created><r:modified>2026-05-11 08:31:23</r:modified></r:article></item><item><title>[vikrant31] autoFlagR 1.0.0</title><author>rathore.vikrant@gmail.com (Vikrant Dev Rathore)</author><description>Automated data quality auditing using unsupervised machine
learning. Provides AI-driven anomaly detection for data quality
assessment, primarily designed for Electronic Health Records
(EHR) data, with benchmarking capabilities for validation and
publication. Methods based on: Liu et al. (2008)
&lt;doi:10.1109/ICDM.2008.17&gt;, Breunig et al. (2000)
&lt;doi:10.1145/342009.335388&gt;.</description><link>https://github.com/r-universe/vikrant31/actions/runs/25955638831</link><pubDate>Sat, 10 Jan 2026 07:42:43 GMT</pubDate><r:package>autoFlagR</r:package><r:version>1.0.0</r:version><r:status>failure</r:status><r:repository>https://vikrant31.r-universe.dev</r:repository><r:upstream>https://github.com/vikrant31/autoflagr</r:upstream></item><item><title>[vikrant31] privacyR 1.0.1</title><author>rathore.vikrant@gmail.com (Vikrant Dev Rathore)</author><description>Tools for anonymizing sensitive patient and research data.
Helps protect privacy while keeping data useful for analysis.
Anonymizes IDs, names, dates, locations, and ages while
maintaining referential integrity. Methods based on: Sweeney
(2002) &lt;doi:10.1142/S0218488502001648&gt;, Dwork et al. (2006)
&lt;doi:10.1007/11681878_14&gt;, El Emam et al. (2011)
&lt;doi:10.1371/journal.pone.0028071&gt;, Fung et al. (2010)
&lt;doi:10.1145/1749603.1749605&gt;.</description><link>https://github.com/r-universe/vikrant31/actions/runs/26357473401</link><pubDate>Mon, 24 Nov 2025 15:19:30 GMT</pubDate><r:package>privacyR</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://vikrant31.r-universe.dev</r:repository><r:upstream>https://github.com/vikrant31/privacyr</r:upstream><r:article><r:source>privacyR.Rmd</r:source><r:filename>privacyR.html</r:filename><r:title>Privacy-Preserving Data Anonymization with privacyR</r:title><r:created>2025-11-24 15:02:18</r:created><r:modified>2025-11-24 15:02:18</r:modified></r:article></item></channel></rss>