P
Paul Rogers Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Biostatistician
faculty
9 h-index
90 pubs
342 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Paul Rogers, a biostatistician at the National Center for Toxicological Research, focuses his research on the application of statistical methods and data mining techniques to analyze health-related data. His work has involved investigating adverse events associated with opioid use, including a specific focus on cardiovascular risks in women and the development of a Charlson Comorbidity Index for the American Indian population using data from the Strong Heart Study. Rogers also studies sex-based differences in the immunotoxicity of silver nanoparticles and leverages artificial intelligence for disease screening among American Indians.
His research utilizes large datasets, such as the Medical Information Mart for Intensive Care (MIMIC) database and the FDA Adverse Event Reporting System (FAERS). Rogers has published numerous papers, with metrics including an h-index of 9 and over 300 citations. He collaborates with researchers at the National Center for Toxicological Research, including Beverly Lyn‐Cook, Wen Zou, Weigong Ge, and Dong Wang.
Metrics
- h-index: 9
- Publications: 90
- Citations: 342
Selected Publications
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women (2025)
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Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study (2025)
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Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study (2024)
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Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex (2024)
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Investigation of sex-based differences in the immunotoxicity of silver nanoparticles (2024)
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A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database (2023)
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Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study (2023)
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Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex (2023)
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Controlling for Confounding in Complex Survey Machine Learning Models to Assess Drug Safety and Risk (2023)
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Assessment of a Modified Sandwich Estimator for Generalized Estimating Equations with Application to Opioid Poisoning in MIMIC-IV ICU Patients (2021)
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Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data (2021)
Collaboration Network
Top Collaborators
Beverly Lyn‐Cook
United States Food and Drug Administration
6 shared publications
In database
- AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
- Investigation of sex-based differences in the immunotoxicity of silver nanoparticles
- RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system
- A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
Showing 5 of 6 shared publications
Dong Wang
National Center for Toxicological Research (US)
4 shared publications
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex
Weida Tong
United States Food and Drug Administration (US)
4 shared publications
- AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
- RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system
- A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
Richardae Araojo
United States Food and Drug Administration (US)
3 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- MSR72 Collaborative, Multisectoral, and Multidisciplinary Approach to Enhance FDA One Health Initiative Communication Strategies
Jessica Reese
University of Oklahoma Health Sciences Center (US)
3 shared publications
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Huixiao Hong
Cancer Research And Biostatistics
3 shared publications
In database
- AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
- RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system
- A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
Weigong Ge
Cancer Research And Biostatistics
3 shared publications
In database
- AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
- RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system
- A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
Wen Zou
Cancer Research And Biostatistics
3 shared publications
In database
- AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women
- RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system
- A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
Dong Wang
National Center for Toxicological Research
2 shared publications
In database
- Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
Zhiyuan Lu
National Center for Toxicological Research (US)
2 shared publications
- Identifying Vulnerabilities to NSAID Adverse Events in the US Population: An Analysis of Pre-Existing Conditions and Sex
- Identifying Vulnerabilities to NSAID Adverse Events in the U.S. Population: An Analysis of Preexisting Conditions and Sex
Christine Merenda
United States Food and Drug Administration (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Christine Lee
Office of Minority Health and Health Equity (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Milena Lolic
Office of Minority Health and Health Equity (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Ying Zhang
University of Oklahoma Health Sciences Center (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
Kimberly Malloy
University of Oklahoma Health Sciences Center (US)
2 shared publications
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
- Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
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