Journals

  • Journal of Healthcare AI and ML

    • Journal of Healthcare AI and ML (JHAM) Journal Summary:

      The Journal of Healthcare AI and ML (JHAM) is a premier international publication dedicated to the convergence of healthcare, artificial intelligence (AI), and machine learning (ML). JHAM serves as a platform for researchers, practitioners, and policymakers to disseminate cutting-edge research findings, innovative methodologies, and transformative applications in the rapidly evolving field of AI and ML in healthcare.

      Scope: JHAM covers a broad spectrum of topics at the intersection of healthcare, AI, and ML, including but not limited to:

      1. Medical Imaging Analysis: Novel AI and ML techniques for medical image segmentation, classification, and interpretation.
      2. Clinical Decision Support Systems: Development and evaluation of AI-driven decision support tools to aid clinicians in diagnosis, treatment planning, and patient management.
      3. Healthcare Data Analytics: Advanced data mining, predictive modeling, and statistical analysis methods for extracting insights from large-scale healthcare datasets.
      4. Personalized Medicine: AI-based approaches for tailoring medical treatments and interventions to individual patients' genetic, clinical, and lifestyle characteristics.
      5. Healthcare Operations Optimization: Optimization models, algorithms, and systems for improving the efficiency, quality, and cost-effectiveness of healthcare delivery processes.
      6. Telemedicine and Remote Patient Monitoring: AI-enabled telehealth solutions for remote consultation, monitoring of chronic conditions, and delivery of personalized healthcare services.
      7. Ethical and Regulatory Issues: Ethical considerations, privacy concerns, and regulatory frameworks pertaining to the use of AI and ML technologies in healthcare.

      Publication Types: JHAM publishes a variety of scholarly works, including:

      1. Original Research Articles: Rigorous empirical studies presenting novel AI/ML methodologies, experimental results, and theoretical insights relevant to healthcare applications.
      2. Review Articles: Comprehensive surveys of the state-of-the-art in specific areas of healthcare AI and ML, providing critical analyses, comparisons of approaches, and future research directions.
      3. Case Studies and Applications: Real-world case studies, use cases, and practical applications showcasing the deployment and impact of AI/ML technologies in clinical settings and healthcare organizations.
      4. Perspectives and Opinion Pieces: Thought-provoking perspectives, editorials, and opinion pieces addressing emerging trends, challenges, and opportunities in healthcare AI and ML.
      5. Letters to the Editor: Brief communications on timely topics, responses to published articles, and discussions on controversial issues in the field.

      Audience: JHAM caters to a diverse audience, including:

      1. Researchers and Academics: Scientists, engineers, and scholars conducting research in AI, ML, healthcare informatics, and related disciplines.
      2. Clinicians and Healthcare Professionals: Physicians, nurses, pharmacists, and other healthcare practitioners interested in leveraging AI/ML technologies to enhance patient care and clinical decision-making.
      3. Industry Professionals: Professionals working in healthcare IT, medical device manufacturing, pharmaceuticals, and healthcare consulting, seeking insights into AI-driven innovations and market trends.
      4. Policymakers and Regulators: Government officials, policymakers, and regulatory agencies involved in shaping healthcare policies, regulations, and standards related to AI and ML applications.
      5. Students and Educators: Graduate students, postdoctoral researchers, and educators seeking educational resources, research opportunities, and career guidance in the field of healthcare AI and ML.

      Editorial Policies:

    • JHAM adheres to the highest standards of editorial integrity, transparency, and peer review. All submitted manuscripts undergo rigorous double-blind peer review by experts in the field to ensure scientific rigor, methodological soundness, and relevance to the journal's scope. The journal follows a transparent and timely review process, providing constructive feedback to authors and striving for excellence in scholarly publishing.

  • International Journal of AI-Assisted Medicine

    International Journal of AI-Assisted Medicine (IJAAM) - Journal Description:

    The International Journal of AI-Assisted Medicine (IJAAM) is a prestigious publication dedicated to advancing the integration of artificial intelligence (AI) technologies into various aspects of medical practice and healthcare delivery. IJAAM provides a comprehensive platform for researchers, clinicians, and industry professionals to disseminate innovative research findings, state-of-the-art methodologies, and transformative applications that harness the power of AI to improve patient care, diagnosis, treatment, and outcomes.

    Mission: IJAAM aims to accelerate the adoption and integration of AI technologies in medicine and healthcare, promoting evidence-based approaches, interdisciplinary collaborations, and ethical considerations. The journal seeks to facilitate knowledge exchange, innovation, and translation of AI research into clinical practice, ultimately enhancing healthcare quality, efficiency, and accessibility worldwide.

    Scope: IJAAM covers a wide range of topics at the intersection of AI and medicine, including but not limited to:

    • AI-driven medical imaging and diagnostics
    • Clinical decision support systems
    • Predictive modeling and risk stratification
    • Precision medicine and personalized treatment
    • Natural language processing in healthcare
    • Health informatics and electronic health records
    • Telemedicine and remote patient monitoring
    • AI ethics, privacy, and regulatory considerations

    Publication Types: IJAAM publishes original research articles, review articles, case studies, and application notes, providing insights into the development, validation, and deployment of AI-assisted medical technologies. The journal also welcomes perspectives, commentaries, and opinion pieces on emerging trends, challenges, and opportunities in AI-assisted medicine.

    Audience: IJAAM caters to a diverse audience, including researchers and academics in AI, machine learning, and medical informatics, healthcare professionals and clinicians, industry professionals in healthcare IT and medical device manufacturing, policymakers and regulators, students, and educators interested in AI-assisted medicine.

  • International Journal of Medical Informatics and AI

    The International Journal of Medical Informatics and AI (IJMIAI) is a prestigious scholarly publication dedicated to exploring the convergence of medical informatics, artificial intelligence (AI), and machine learning (ML). IJMIAI provides a platform for researchers, practitioners, and policymakers to disseminate high-quality research findings, innovative methodologies, and transformative applications in the dynamic and interdisciplinary field of medical informatics and AI.

    Scope: IJMIAI covers a broad spectrum of topics related to the application of AI and ML in healthcare and medical informatics, including but not limited to:

    1. Health data analytics and mining
    2. Clinical decision support systems
    3. Electronic health records and interoperability
    4. Telemedicine and remote patient monitoring
    5. Health informatics standards and interoperability
    6. AI-driven medical imaging analysis
    7. Natural language processing in healthcare
    8. Health information privacy and security
    9. AI-based personalized medicine
    10. Healthcare quality improvement and patient safety

    Publication Types: IJMIAI publishes original research articles, review articles, case studies, and application notes, providing a comprehensive and multidisciplinary view of the latest advancements and trends in medical informatics and AI. The journal also welcomes perspectives, commentaries, and opinion pieces addressing emerging issues and challenges in the field.

    Audience: IJMIAI caters to a diverse audience, including:

    1. Researchers and academics in medical informatics, AI, and ML
    2. Healthcare professionals and clinicians interested in leveraging AI technologies
    3. Health IT professionals and informaticians involved in healthcare system design and implementation
    4. Industry professionals in healthcare IT, medical device manufacturing, and pharmaceuticals
    5. Policymakers, regulators, and public health officials shaping healthcare policies and regulations
    6. Students and educators seeking knowledge and insights into medical informatics and AI applications in healthcare

    Editorial Team: The editorial team of IJMIAI comprises leading experts and scholars in medical informatics, AI, and healthcare. Led by an Editor-in-Chief and supported by Associate Editors, Editorial Board Members, and Reviewers, the team ensures the rigorous peer review process and maintains the highest standards of scientific integrity and editorial excellence.

    Mission: The mission of IJMIAI is to advance the frontier of knowledge at the intersection of medical informatics and AI, promote interdisciplinary research collaborations, and facilitate the translation of innovative technologies into clinical practice for improving patient care, healthcare delivery, and population health outcomes globally.

  • Journal of Healthcare Data Science and AI

    Journal of Healthcare Data Science and AI (JHDSA) - Journal Description:

    The Journal of Healthcare Data Science and AI (JHDSA) is a cutting-edge publication dedicated to the intersection of healthcare, data science, and artificial intelligence (AI). JHDSA provides a premier platform for researchers, practitioners, and policymakers to disseminate innovative research findings, methodologies, and applications that leverage data science and AI to address key challenges and opportunities in healthcare.

    Mission: JHDSA aims to advance the science and practice of healthcare data analytics, artificial intelligence, and machine learning. The journal seeks to promote interdisciplinary collaborations, foster innovation, and facilitate the translation of data-driven insights into actionable strategies for improving patient outcomes, healthcare delivery, and population health.

    Scope: JHDSA covers a broad range of topics related to healthcare data science and AI, including but not limited to:

    • Big data analytics in healthcare
    • Predictive modeling and machine learning algorithms
    • Clinical decision support systems
    • Electronic health records and health informatics
    • Healthcare data privacy and security
    • Patient-centered outcomes research
    • Population health management
    • Healthcare operations optimization

    Publication Types: JHDSA publishes original research articles, review articles, case studies, and application notes, providing a comprehensive overview of the latest advancements and trends in healthcare data science and AI. The journal also welcomes perspectives, opinion pieces, and industry insights on emerging issues and opportunities in the field.

    Audience: JHDSA caters to a diverse audience, including researchers and academics in data science, AI, and healthcare informatics, healthcare professionals and clinicians, industry professionals in healthcare IT and analytics, policymakers and regulators, students, and educators interested in healthcare data science and AI applications.

  • AI Applications in Healthcare

    AI Applications in Healthcare (AIH) - Journal Description:

    AI Applications in Healthcare (AIH) is a cutting-edge international journal dedicated to the practical applications of artificial intelligence (AI) in various aspects of healthcare delivery. AIH serves as a premier platform for researchers, practitioners, and industry experts to disseminate innovative AI-driven solutions, successful case studies, and best practices aimed at improving patient outcomes, healthcare operations, and clinical decision-making.

    Scope: AIH covers a wide range of topics related to the practical applications of AI in healthcare, including but not limited to:

    1. Medical imaging analysis: AI-based techniques for medical image interpretation, diagnosis, and treatment planning.
    2. Clinical decision support systems: AI-driven tools and algorithms to assist healthcare providers in making accurate and timely clinical decisions.
    3. Healthcare operations optimization: AI applications for streamlining hospital workflows, resource allocation, and patient scheduling.
    4. Predictive analytics: AI models for forecasting disease trends, patient outcomes, and healthcare resource utilization.
    5. Drug discovery and development: AI-driven approaches for drug design, virtual screening, and personalized medicine.
    6. Remote patient monitoring: AI-enabled technologies for remote monitoring of patient health, chronic disease management, and telehealth.
    7. Healthcare chatbots and virtual assistants: AI-powered conversational agents for patient engagement, health information retrieval, and triage.
    8. Ethical and regulatory considerations: Ethical implications, privacy concerns, and regulatory frameworks for the responsible use of AI in healthcare.

    Publication Types: AIH publishes original research articles, review articles, case studies, and application notes, providing insights into the development, implementation, and evaluation of AI applications in healthcare. The journal also welcomes perspectives, opinion pieces, and industry insights on emerging trends and challenges in the field.

    Audience: AIH caters to a diverse audience, including researchers and academics in AI, machine learning, and healthcare informatics, healthcare professionals and clinicians, industry professionals in healthcare IT and medical device manufacturing, policymakers and regulators, students, and educators interested in healthcare AI applications.

    Editorial Team: The editorial team of AIH comprises esteemed experts and thought leaders in AI, healthcare, and related fields. Led by Editor-in-Chief Dr. [Insert Name], the team ensures the rigor and relevance of published research, maintaining the highest standards of scientific integrity and editorial excellence.

    Mission: The mission of AIH is to bridge the gap between AI research and real-world healthcare implementations by showcasing successful AI applications, case studies, and best practices. AIH aims to accelerate the adoption of AI-driven solutions in healthcare settings worldwide, ultimately improving patient care, reducing healthcare costs, and advancing population health outcomes.