Daniel Berleant Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Little Rock

faculty

19 h-index 123 pubs 1,726 cited

Research Areas

Meta-analysis and systematic reviews Natural Language Processing Techniques Emergency and Acute Care Studies Advanced Neural Network Applications Technology Adoption and User Behaviour Healthcare Policy and Management

Links

Lab Website

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OverviewAI-generated summary

Daniel Berleant's research focuses on the application of computational methods and data analysis to address complex problems, particularly within healthcare and technology forecasting. He has published extensively on topics including discrete-event simulation for healthcare operations, the automation of systematic literature reviews using natural language processing and text mining, and quantitative methods for technology trend extrapolation. His work also investigates the robustness of deep learning classifiers and the assessment of image quality in datasets affected by noise.

Berleant collaborates with researchers across institutions, including Peng-Hung Tsai and Michael Howell at the University of Arkansas at Little Rock, and Richard S. Segall from Arkansas State University, with whom he has co-authored multiple publications. His scholarship metrics include an h-index of 19, with over 123 publications and 1,726 citations. He is noted as recently active, with publications extending to 2025.

Metrics

  • h-index: 19
  • Publications: 123
  • Citations: 1,726

Selected Publications

  • Epidemiology, risk factors, and prevention strategies of multiple myeloma cancer: a systematic review (2025) DOI
  • How Does Age at Diagnosis Influence Multiple Myeloma Survival? Empirical Evidence (2025) DOI
  • Start Time End Time Integration (STETI): Method for Including Recent Data to Analyze Trends in Kidney Cancer Survival (2025) DOI
  • An Information Quality Framework for Managed Health Care (2024) DOI
  • Predicting Future Participation of Women in Space by Analyzing Past Trends (2024) DOI
  • A Customer Service Chatbot Using Python, Machine Learning, and Artificial Intelligence (2024) DOI
  • A Customer Service Chatbot Using Python, Machine Learning, and Artificial Intelligence (2024) DOI
  • ASI: Accuracy-Stability Index for Evaluating Deep Learning Models (2023) DOI
  • ASI: Accuracy-Stability Index for Evaluating Deep Learning Models (2023) DOI
  • Using Discrete-Event Simulation to Balance Staff Allocation and Patient Flow between Clinic and Surgery (2023) DOI
  • Visual Question Answering (VQA) on Images with Superimposed Text (2023) DOI
  • Automating Systematic Literature Reviews with Natural Language Processing and Text Mining: A Systematic Literature Review (2023) DOI
  • Data Science Knowledge and Skills That Reliability Engineers Need: A Survey (2023) DOI
  • Quantitative Technology Forecasting: A Review of Trend Extrapolation Methods (2023) DOI
  • Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets (2022) DOI

Collaborators

Researchers in the database who share publications

Peng-Hung Tsai University of Arkansas at Little Rock 10 shared publications Richard S. Segall Arkansas State University 10 shared publications Michael Howell University of Arkansas at Little Rock 5 shared publications Michael Bauer University of Arkansas for Medical Sciences 2 shared publications Girish Sundaram University of Arkansas at Little Rock 2 shared publications Phillip Farmer University of Arkansas for Medical Sciences 1 shared publication Cody Ashby University of Arkansas for Medical Sciences 1 shared publication Ahmed Abuhalimeh University of Arkansas at Little Rock 1 shared publication

Similar Researchers

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JJ Rivera Arkansas Tech University
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Saima Absar University of Arkansas at Fayetteville
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