Shake Ibna Abir Data-verified

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

Researcher

Last publication 2025 Last refreshed 2026-05-16

faculty

9 h-index 17 pubs 154 cited

Biography and Research Information

OverviewAI-generated summary

Shake Ibna Abir's research focuses on the application of machine learning and deep learning techniques across various domains, including health, environmental sustainability, and financial accessibility. In health sciences, Abir investigates the use of AI for diagnosing and predicting neurological diseases and skin lesions, with a specific emphasis on melanoma detection and brain tumor identification through MR imaging. This work also extends to studying health risks and disease transmission in undocumented immigrant populations using predictive machine learning models. Abir also examines the influence of AI innovation and financial accessibility on environmental sustainability, particularly within the G-7 nations, employing econometric methods like Panel ARDL and Quantile Regression. Further research explores the nexus between AI innovation, ecological footprints, and financial factors in the Nordic region, as well as the impact of AI and financial accessibility on load capacity factors in the United States. Abir holds a h-index of 8 with 114 citations across 13 publications and collaborates with Shaharina Shoha from Arkansas State University on multiple projects.

Metrics

  • h-index: 9
  • Publications: 17
  • Citations: 154

Selected Publications

  • Challenges and Advances in Different Feature Fusion Techniques: Exploring Mechanisms and Applications (2025)
  • Integrating and Enhancing Diverse Categories of Medical Data for AI-Driven Healthcare Solutions (2025)
  • Utilization of Feature Fusion in Diagnostic Applications (2025)
  • Artificial Intelligence in Multi-Disease Medical Diagnostics: An Integrative Approach (2025)
    5 citations DOI OpenAlex
  • Advancing Neurological Disease Prediction through Machine Learning Techniques (2025)
    11 citations DOI OpenAlex
  • EEG Functional Connectivity and Deep Learning for Automated Diagnosis of Alzheimer's disease and Schizophrenia (2025)
    9 citations DOI OpenAlex
  • Machine Learning and Deep Learning Techniques for EEG-Based Prediction of Psychiatric Disorders (2025)
    17 citations DOI OpenAlex
  • Comparative Analysis of Currency Exchange and Stock Markets in BRICS Using Machine Learning to Forecast Optimal Trends for Data-Driven Decision Making (2025)
    1 citation DOI OpenAlex
  • Deep Learning for Financial Markets: A Case-Based Analysis of BRICS Nations in the Era of Intelligent Forecasting (2025)
    9 citations DOI OpenAlex
  • Accelerating BRICS Economic Growth: AI-Driven Data Analytics for Informed Policy and Decision Making (2024)
    9 citations DOI OpenAlex
  • Use of AI-Powered Precision in Machine Learning Models for Real-Time Currency Exchange Rate Forecasting in BRICS Economies (2024)
    9 citations DOI OpenAlex
  • Deep Learning Application of LSTM(P) to predict the risk factors of etiology cardiovascular disease (2024)
    8 citations DOI OpenAlex
  • Precision Lesion Analysis and Classification in Dermatological Imaging through Advanced Convolutional Architectures (2024)
    11 citations DOI OpenAlex
  • Deep Learning-Based Classification of Skin Lesions: Enhancing Melanoma Detection through Automated Preprocessing and Data Augmentation (2024)
    15 citations DOI OpenAlex
  • Deep Neural Networks in Medical Imaging: Advances, Challenges, and Future Directions for Precision Healthcare (2024)
    15 citations DOI OpenAlex

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Collaboration Network

33 Collaborators 22 Institutions 4 Countries

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