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AAIML( SCOPUS/ESCI) 2025 : Advances in Artificial Intelligence and Machine Learning (ISSN: 2582-9793, Scopus Source Id: 21101164612)

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Link: https://www.oajaiml.com/
 
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Submission Deadline May 30, 2025
Categories    artificial intelligence   machine learning   ai in medicine   ai in healthcare
 

Call For Papers

Advances in Artificial Intelligence and Machine Learning (ISSN: 2582-9793, Scopus Source id: 21101164612) is pleased to invite you to submit an original manuscript for consideration in the upcoming Volume 5, Issue 3.


We have recently released Volume 5, Issue 1, which is ready for inspection. https://www.oajaiml.com/current-issue


Journal Highlights:

Editor-in-Chief: Prof. Anca L. Ralescu.
Indexing: Web of Science, Scopus, DBLP, Road, ISSN, DOI, Scilicit, Crossreff, Google Scholar, Europub, Cosmos, CiteScore: 1.0. SJR:0.170, Q4.
Submission Date: 30 August 2025
Discount: 20% discount if manuscript submitted on or before submission 30-May-2025.

We are inviting articles in the form of original research articles, reviews, short communications, mini reviews, etc.


For more information, please refer to our author guidelines and FAQ page for quick answers.


We look forward to receiving your manuscript and appreciate your consideration.




The topics covered by the Journal include but are not limited to:

Artificial Intelligence – Theory and Practice
Approximate and Probabilistic Reasoning
Artificial Intelligence in Medicine and Healthcare
Autonomous Vehicles
Big Data
Bioinformatics
Biometric Systems
Brain Computer Interface
Computational Intelligence
Computer Visions
Distributed Artificial Intelligence
Deep Learning
Evolutionary Systems
Fuzzy Systems
Genetic Algorithms
Graphical Models in Machine Learning
Human-computer Interface including Assistive Systems
Image Processing and Understanding
Knowledge-based and agent-based systems
Kernel Methods in Machine Learning
Natural Language Processing and Understanding
Neural Networks
Optimization
Planning and Scheduling
Pattern Recognition
Quantum Methods in Machine Learning
Robotics
Statistical Learning Theory

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