ISSN :2582-9793

Welcome to the Advances in Artificial Intelligence and Machine Learning (AAIML) - An Artificial Intelligence Journal

AAIML is a global, peer-reviewed, open access online journal, committed to timely publication of original work in Artificial Intelligence, Machine Learning and its related applications. Join the Journal and share your original research..

Our aim is to publish high-quality research in artificial intelligence and machine learning

AAIML publishes Issues six times a year and is committed to a timely peer review process of six to ten weeks from the initial paper submission..

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About Journal

Advances in Artificial Intelligence and Machine Learning (ISSN: 2582-9793; Scopus Source Id: 21101164612) is a global, peer-reviewed, open-access international journal indexed in Web of Science (Impact Factor= 0.5)Scopus (CiteScore: 1.4, H-Index = 5).  The Journal is committed to the timely publication of original work in Artificial Intelligence and Machine Learning. In addition to original research, the journal encourages review papers, including mini reviews focused on a very specific topic. The mission of the Advances in Artificial Intelligence and Machine Learning is to provide a context for the study of Artificial Intelligence and Human Wellbeing, Human Cognition, Artificial Systems, Autonomous Machines, etc. From 2026 onwards, the Journal publishes 6 Issues per Year (February, April, June, August, October, December).

Online Submission Link Read More 

Response from Scopus Confirming the ACTIVE status of the Journal



The Journal is Currently Indexed in Scopus. Scopus coverage-year information is updated once a year by Scopus, typically in May–June each year. Visitors can verify the journal’s active status in the Scopus Source Title List by visiting the official Scopus content page:



Journal policy on AI-generated submissions 

AI-generated papers will be rejected immediately without any review. The journal will keep a record of such papers and their authors.

WELCOME MESSAGE FROM EDITOR-IN-CHIEF
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Welcome to the Advances in Artificial Intelligence and Machine Learning (AAIML) journal. Launched in February 2021, the journal has seen a steady increase in the number of high-quality submissions. Thanks are due to the authors, editors, and anonymous reviewers, who have contributed to the successful publication of very interesting research articles.

AAIML aims to publish original contributions in artificial intelligence and machine learning. Authors are invited to contribute full-length research papers, systematic review papers, and proposals for special issues. AAIML is published six times a year and continues to be committed to a timely peer review process of six to ten weeks from the initial paper submission.

Sincerely,
Anca Ralescu
Anca.Ralescu@uc.edu
Senior Member, IEEE
EECS Department, University of Cincinnati, ML 0030
Cincinnati, OH 45221-0030, USA
Editor-in-Chief


Indexing and Services
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Editorial Board
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Anca L. Ralescu
Editor in Chief

Anca.Ralescu@uc.edu

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Jeffrey E. Arle

jarle@bidmc.harvard.edu

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William Cheng-Chung Chu

cchu@thu.edu.tw

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Andrew A. Goldenberg

golden@mie.utoronto.ca

Recently published articles
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Original Research
Detecting Anomalous States Through File Operations Using Unsupervised Learning Algorithms

DOI : https://dx.doi.org/10.54364/AAIML.2026.62284
02-Mar-2026
Islambek Saymanov, Firdavs Muxammadiev, Gayrat Juraev, Yebo Lu, Olga Boiprav, Ruhillo Alaev, Obidjon Bozorov, Timur Abdullayev

PDF Abstract

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Original Research
Glaucoma Diagnosis via Advanced Retinal Image Processing and V-RACNet Classification

DOI : 10.54364/AAIML.2026.61283
26-Feb-2026
VIJAYA MADHAVI VUPPU, P Lalitha Surya Kumari.

PDF Abstract

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Original Research
The Role of Digital Learning Innovations in Strengthening Human Capital: A Mixed Educational and Corporate Perspective

DOI : 10.54364/AAIML.2026.61282
25-Feb-2026
Nikola Staffenova, Milan Kubina, Dominika Dupakova.

PDF Abstract

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Original Research
Epilepsy Seizure Prediction using an SVM Algorithm

DOI : 10.54364/AAIML.2026.61281
24-Feb-2026
Asam Almohamed, Akeel Abdulkareem Alsakaa, Mohsin Hasan Hussien, Hazim Alsaqaa, Kesra Nermend

PDF Abstract

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Original Research
DeepCryptanalysis: Breaking Chaos-Based Color Image Encryption with a Dense Attention U-Net

DOI : 10.54364/AAIML.2026.61280
22-Feb-2026
Sonia Amiri, Mourad Zaied.

PDF Abstract