Richard S. Segall Source Confirmed

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

Researcher

Arkansas State University

faculty

10 h-index 114 pubs 429 cited

Research Areas

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OverviewAI-generated summary

Richard S. Segall's research interests encompass the application of artificial intelligence, machine learning, and data processing techniques across various domains. His recent publications include work on quantitative technology forecasting, image processing for plant disease detection, and the development of customer service chatbots utilizing AI and machine learning. Segall has also explored the use of neural networks and machine learning for predicting infectious diseases, including COVID-19, and surveyed open-source statistical software. His scholarship metrics indicate an h-index of 10 with 429 total citations across 114 publications. Segall has established collaborative research relationships with faculty at the University of Arkansas at Little Rock, including Daniel Berleant (10 shared publications), Peng-Hung Tsai (7 shared publications), and Michael Howell (5 shared publications), as well as Vidhya Sankarasubbu at Arkansas State University (2 shared publications).

Metrics

h-index: 10
Publications: 114
Citations: 429

Selected Publications

The Convergence of Big Data and AI Through Learning-Based Methods for Business Intelligence (2026) DOI
Unified Federated AI Framework for Credit Scoring (2026) DOI
Comparative Analysis of Edge vs. Cloud Contact Center Deployments: A Technical and Architectural Perspective (2025) DOI
Case Study on Understanding the Power of Retrieval Augmented Generation (RAG) (2025) DOI
Big Data Integration in Genomic Analysis (2025) DOI
Abstract P3086: Future Heart Motion Measurements in Deep Learning-based Predictive Imaging (2025) DOI
Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use? (2024) DOI
Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases (2024) DOI
Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants (2024) DOI
Image Processing of Big Data for Plant Diseases of Four Different Plant Categories (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
Extract Clinical Lab Tests From Electronic Hospital Records Through Featured Transformer Model (2024) DOI
What is ChatGPT and its Present and Future for Artificial Intelligence in Trans-Disciplinary Communications? (2023) DOI