Aims and Scope

The Journal of Artificial Intelligence Applications and Data Science (JAIADS) serves as a leading platform for the dissemination of high-impact research at the nexus of computational intelligence and real-world problem-solving. We invite original, high-quality research papers that bridge the gap between theoretical advancements and practical implementations. Our scope is intentionally broad yet distinctly focused on how Artificial Intelligence (AI), Machine Learning (ML), and Data Science methodologies are actively transforming scientific, industrial, and societal domains. The journal welcomes submissions spanning – but not strictly limited to – the following core areas:

 

I.  AI in Biomedical Engineering:

  1. Medical image analysis and computer-aided diagnosis (segmentation, classification, and detection across MRI, CT, X-ray, and ultrasound)
  2. Biomedical signal processing with machine learning (ECG, EEG, EMG, and physiological time-series analysis)
  3. AI for disease prediction, risk stratification, and clinical decision support
  4. AI-driven medical robotics and intraoperative/surgical guidance systems
  5. Wearable sensors, remote patient monitoring, and the Internet of Medical Things (IoMT)
  6. Bioinformatics approaches for genomic and proteomic sequence analysis using AI (NGS data processing, sequence alignment, variant calling, and deep learning–based gene/protein expression prediction).
  7. Bioinformatics-driven molecular docking, structural analysis, and computational drug design (protein structure/function prediction and molecular modeling for drug discovery)
  8. Bioinformatics database mining and software tool development using machine learning (algorithm development for sequence/database mining, annotation pipelines, and explainable AI in genomic analysis)
  9. Bioinformatics methods in phylogenetics, comparative genomics, and evolutionary sequence analysis (construction of phylogenetic trees, evolutionary relationship inference, and comparative genome analysis using computational methods)
  10. Bioinformatics pipelines for single-cell omics and transcriptomic data analysis (computational pipelines for single-cell RNA-seq, cell clustering, and trajectory inference using machine learning)

        II.  AI in Engineering Applications:

  1.  AI for predictive maintenance, fault diagnosis, and prognostics in industrial systems
  2.  Machine learning for structural health monitoring and civil infrastructure
  3. Intelligent control, optimization, and reinforcement learning for automation
  4.  AI in smart manufacturing, Industry 4.0, and digital twins
  5. Computer vision for inspection, quality control, and defect detection
  6. AI for power systems, smart grids, and energy management
  7.  Autonomous systems, robotics, and intelligent transportation
  8.  AI-driven design optimization and generative engineering design
  9.  Edge AI, embedded intelligence, and resource-constrained deployment
  10.  AI for network security, intrusion detection, and SDN/IoT systems

      III.  Data Science:

  1. Big data analytics, scalable computing, and distributed processing frameworks
  2.  Statistical learning, predictive modeling, and supervised methods
  3. Unsupervised learning, clustering, and dimensionality reduction
  4. Time-series analysis and forecasting
  5.  Natural language processing and text mining
  6.  Data mining, knowledge discovery, and pattern recognition
  7. Data visualization and exploratory data analysis
  8.  Data engineering, data quality, preprocessing, and feature engineering
  9. Causal inference, explainability, and interpretable machine learning
  10. Ethics, fairness, privacy, and governance in data-driven systems

Article Types Accepted

  • Original Research Articles: Comprehensive studies detailing novel methodologies or significant experimental results. (review papers are not excpted)

 

By publishing rigorous, validated research, JAIADS aims to be an indispensable resource for academics, industry professionals, and policymakers navigating the future of intelligent technologies.