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Call for Research Papers IJAIS  ·  Peer-Reviewed Journal

Advancing Research in Artificial Intelligence & Machine Learning

The International Journal of Applied Information Systems (IJAIS) invites researchers, academicians, and industry professionals to submit high-quality original research in Artificial Intelligence, Machine Learning, Deep Learning, Data Science, and Intelligent Information Systems. We particularly welcome innovative methodologies, experimental studies, interdisciplinary applications, and research addressing real-world challenges through intelligent computing technologies.

Research Areas of Interest
Generative AI & LLMs Machine & Deep Learning Natural Language Processing Computer Vision Explainable & Trustworthy AI AI in Healthcare Predictive Analytics Intelligent Systems AI in Finance & Business Data Science & Big Data
Submission Deadline 30 November 2026
IJAIS IJAIS IJAIS IJAIS

IJAIS is now being indexed with Google Scholar, Informatics, ProQuest CSA Technology Research Database, NASA ADS, CiteSeer, UlrichWeb, ScientificCommons (Univ. of St Gallens), University of Karlsruhe, Germany, PennState University
● SUBMISSIONS OPEN

Call for Papers

IJAIS invites original research in AI, Machine Learning, Data Science and Applied Information Systems for its upcoming edition.

Submit Your Manuscript View Call for Papers

Manuscripts undergo editorial screening and peer review.

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The International Journal of Applied Information Systems in association with indexing partners Google Scholar, Elsevier CiteuLike et. al. publishes original papers in applied, experimental and theoretical aspects of information systems. The enhanced online publication platform is jointly developed with support from the Foundation of Computer Science, New York, USA.

All published research articles in IJAIS academic research journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees. The camera-ready is ratified by FCS reviewer network.

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Proceedings

Recent articles

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ARTICLE
A Review of Machine Learning and Deep Learning Techniques for Financial Risk Assessment: Loan Default Prediction and Fraud Detection

Ayodeji Olusegun Akinwumi, Samuel Adebayo Oluwadare, Ilobekemen Perpetual Oladoja, Hussein Oluwaponmile Adefuwa

Loan Default Prediction Credit Risk Financial Fraud Ensemble Learning Recurrent Neural Networks Hybrid Models Class Imbalance Synthetic Data Explainable AI
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ARTICLE
Methodology for Developing and Optimizing Web Applications Based on Java and JavaScript Technologies

Olena Komleva

Java; JavaScript; web application development; web application optimization; software engineering methodology; automated testing; performance engineering; observability; maintainability; empirical synthesis
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ARTICLE
Multi-Label Machine Learning Framework for Homoeopathic Remedy Recommendation using Clinical Disease Descriptions

Rincy T.A.

Machine Learning Homoeopathic Remedy Recommendation Multi-label Classification TF-IDF Natural Language Processing
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ARTICLE
A Comprehensive Review of the Yorùbá Numbering Scheme: Linguistic Structure, Computational Modelling, and Digital Preservation

R.K. Adeeyo, O.A. Ọdẹ́jọbí, A.B. Olorunlomerue, J.A. Hassan

Yorùbá numbering scheme linguistic structure computational modelling digital preservation

University affiliates

Penn university journal
The PennState University Libraries comprise 36 libraries at 24 locations throughout the Commonwealth of Pennsylvania. IJAIS releases the articles to PennState University via CSA enterprises.
Washington university journal
The University of Washington host the complete bibliography including the abstracts of the IJAIS published articles via OAIster database. The hosting rights are also available with Worldcat.org via OAIster.
Georgetown University journal
The IJAIS article abstracts are citable from the Library Catalog of Georgetown University. The university affiliates can subscribe directly from the library repository.
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