About VJASH

AIM AND SCOPE

The Virosa Journal of AI in Science and Healthcare (VJASH) is an international, peer-reviewed, open-access journal dedicated to advancing innovation and scholarly research at the intersection of artificial intelligence (AI), medicine, science, and healthcare.

The journal provides a rigorous academic platform for disseminating high-quality research addressing both the transformative opportunities and emerging challenges of AI technologies in clinical practice, biomedical research, and scientific discovery.

VJASH welcomes:

  • Original Research Articles

  • Systematic Reviews & Meta-Analyses

  • Technical Reports

  • Case Studies

  • Perspectives & Commentaries

  • Short Communications

  • Editorials

All submissions undergo double-blind peer review, ensuring scientific integrity, transparency, and relevance for researchers, clinicians, policymakers, engineers, and industry leaders worldwide.

Scope of the Journal

VJASH covers interdisciplinary research across, but not limited to, the following areas:

  • AI applications in clinical diagnostics, medical imaging, and decision-support systems

  • Machine learning and big data analytics in biomedical and health sciences

  • AI-driven drug discovery, personalised medicine, and precision healthcare

  • Robotics, intelligent systems, and automation in healthcare delivery

  • Ethical, legal, regulatory, and policy considerations in AI deployment

  • Societal, scientific, and technological impacts of AI in medicine and research

Key Research Areas

AI for Science & Healthcare

1. AI Driven Diagnostics and early detection

  • Medical imaging (radiology, pathology, ophthalmology)

  • Signal analysis (ECG, EEG, wearable sensors)

  • Multimodal diagnostic models (imaging + laboratory + clinical notes)

  • Early detection of cancer, cardiovascular disease, and neurodegenerative disorders

2. Precision Medicine & Genomics

  • AI for genomic sequencing interpretation

  • Molecular signature-based treatment prediction

  • Pharmacogenomics and individualized drug dosing

  • AI-guided oncology treatment planning

3. Drug Discovery & Computational Biology

  • Generative AI for molecular design

  • Protein structure prediction and simulation

  • AI-accelerated clinical trial optimization

  • Target identification and biomarker discovery

4. Clinical Decision Support & Workflow Automation

  • Ambient clinical documentation (AI medical scribes)

  • Risk stratification and triage systems

  • Predictive analytics for hospital operations

  • AI-assisted electronic health record (EHR) navigation

5. AI in Public Health & Population Health

  • Epidemiological modeling and outbreak prediction

  • Surveillance systems and health monitoring

  • Social determinants of health modeling

  • Health equity analytics

6. Explainable, Trustworthy & Ethical AI

  • Bias detection and mitigation

  • Model interpretability and transparency

  • Regulatory science and AI governance frameworks

  • Safety, validation, and robustness of clinical AI systems

7. AI in Biomedical Research & Scientific Discovery

  • AI-driven hypothesis generation

  • Simulation of physical, chemical, and biological systems

  • Autonomous laboratories (“self-driving labs”)

  • Large-scale scientific data mining

8. Robotics & Intelligent Systems in Healthcare

  • AI-guided surgical robotics

  • Rehabilitation and assistive robotics

  • Intelligent systems for aging populations

  • Hospital logistics and automation robots

9. AI for Education, Training & Scientific Publishing

  • AI-enhanced medical education

  • Simulation-based clinical training

  • AI-assisted scientific writing and peer review

  • Digital transformation in academic publishing

10. Multimodal & Foundation Models for Healthcare

  • Large language models integrated with imaging, genomics, and EHR data

  • Agentic AI for clinical workflows

  • Domain-specific medical foundation models (Med-LLMs)

  • Safety, alignment, and governance for clinical AI systems

Commitment to Open Access and Ethics

Open Access

All articles are published under the Creative Commons Attribution (CC BY 4.0) license, ensuring immediate, free, and unrestricted global access without subscription barriers.

Academic Rigor

All submissions undergo double-blind peer review conducted by subject-matter experts.

Ethical Standards

VJASH follows international publishing best practices aligned with:

  • Committee on Publication Ethics (COPE)

  • International Committee of Medical Journal Editors (ICMJE)

  • Directory of Open Access Journals (DOAJ)

Global Collaboration

The journal encourages submissions from researchers, clinicians, engineers, computer scientists, policymakers, and interdisciplinary scholars worldwide.

Publication Frequency

VJASH follows an annual publication schedule, publishing one volume per year to maintain high editorial and peer-review standards.

Manuscript Submission

Authors are invited to submit manuscripts through the journal’s online submission system available on the VJASH website.

Submissions must:

  • Be original and unpublished

  • Not be under consideration elsewhere

  • Follow the Author Guidelines provided on the website

For inquiries or submission-related issues, please contact: [email protected]