Ahmad Baghal Institution Verified

Sourced from institutional research profiles (UAMS TRI or ARA).

Assistant Professor

University of Arkansas for Medical Sciences

faculty

7 h-index 19 pubs 242 cited

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Biography and Research Information

OverviewAI-generated summary

Ahmad Baghal's research focuses on the application of informatics and data governance strategies within health sciences research. He investigates methods for pseudonymizing participant identification in multi-study research environments and implementing data governance with privacy-preserving record linkages. His work includes exploring the relationship between HDL cholesterol levels and susceptibility to COVID-19 infection, as well as examining brain metabolic fingerprinting for predicting major depression in multiple myeloma patients.

Baghal also studies the influence of care delivery teams on hospitalization outcomes for patients with multimorbidity, highlighting the implications for clinical informatics. He has contributed to understanding how to cultivate informatics capacity within learning health systems. His scholarship metrics include an h-index of 7 with 242 total citations across 19 publications. He collaborates with researchers at the University of Arkansas for Medical Sciences, including Bradley C. Martin, Mandana Rezaeiahari, J. Mick Tilford, and Anthony Goudie, with whom he shares multiple publications.

Metrics

  • h-index: 7
  • Publications: 19
  • Citations: 242

Selected Publications

  • Linking <i>The Cancer Imaging Archive</i> and <scp>GenBank</scp> to the <scp>National Clinical Cohort Collaborative</scp> (2024) DOI
  • Implementing Data Governance with Multi-Modal Privacy-Preserving Record Linkages between Restricted and Public Open Enclaves (2024) DOI
  • In-Hospital Mortality by Race and Ethnicity Among Hospitalized COVID-19 Patients Using Data From the US National COVID Cohort Collaborative (2024) DOI
  • In-Hospital Mortality by Race and Ethnicity Among Hospitalized Covid-19 Patients Using Data from the Us National Covid Cohort Collaborative (2023) DOI
  • Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics (2023) DOI
  • Cultivating informatics capacity for multimorbidity: A learning health systems use case (2022) DOI
  • HDL cholesterol levels and susceptibility to COVID-19 (2022) DOI
  • Higher HDL Cholesterol Levels Decrease Susceptibility to COVID-19 Infection (2022) DOI
  • Resting-state brain metabolic fingerprinting clusters (biomarkers) and predictive models for major depression in multiple myeloma patients (2021) DOI
  • API Driven On-Demand Participant ID Pseudonymization in Heterogeneous Multi-Study Research (2021) DOI

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