Call for Papers
Holistic, Reliable and Effective Artificial Intelligence in Healthcare from a Holistic AI Perspective
Dear researchers, academics, clinicians, IT specialists and healthcare technology stakeholders,
Health informatics is no longer a field limited solely to data management, software development or decision support systems in the digital transformation of healthcare. Artificial intelligence, big data, clinical decision support systems, electronic health records, wearable technologies, multi-omic data, medical imaging, natural language processing and generative AI applications are reshaping every stage of healthcare.
This transformation must be considered not merely in terms of algorithmic success, but in conjunction with the dimensions of ethics, reliability, explainability, clinical applicability, data quality, patient safety, human–AI collaboration, sustainability and governance. For this reason, the scientific framework of the Medical Informatics Congress 2026 is based on “Holistic AI”, that is, a comprehensive approach that evaluates artificial intelligence in healthcare across its technical, clinical, ethical, legal, social and operational dimensions.
Discussions on trustworthy artificial intelligence in healthcare require a comprehensive assessment of multifaceted issues such as data quality, algorithmic bias, transparency, explainability, ethical governance and human oversight. The literature also emphasises that trustworthy medical artificial intelligence cannot be reduced solely to model performance; rather, data, models, clinical context, ethical principles and governance processes must be addressed collectively.
In this context, our conference is opening up a discussion on artificial intelligence applications in healthcare, not only by asking ‘how accurate are the predictions?’, but also by addressing the following questions:
- Can this system really be integrated into the clinical workflow?
- Is it reliable from the perspective of the doctor, the patient and the healthcare organisation?
- Is it explainable, verifiable and traceable?
- How are bias, errors, hallucinations and data security risks managed?
- How does the AI output generated translate into benefits for patients, improvements in the quality of healthcare, and wider societal benefits?
At this year’s conference, we invite all researchers working in the field of medical informatics to present their original work, which examines the technical achievements of artificial intelligence in healthcare alongside clinical value, ethical responsibility and sustainable implementation.
Conference Paper Topics
Our conference will accept original research, applied research, review articles, method development, system design, case studies and experience reports under the following headings:
Artificial Intelligence in Healthcare and Clinical Decision Support
- Clinical decision support systems
- Explainable artificial intelligence and interpretable models
- Machine learning and deep learning applications
- The use of generative artificial intelligence and large language models in healthcare
- Diagnosis, prognosis, risk assessment and treatment response modelling
- AI-powered triage, monitoring and patient management
- Human–AI collaboration and clinical decision-making processes
Holistic AI, Trustworthy Artificial Intelligence and Governance
- Holistic artificial intelligence frameworks in healthcare
- Trustworthy, ethical and responsible artificial intelligence
- Artificial intelligence governance and risk management
- Algorithmic bias, justice and health inequalities
- Model monitoring, performance drift and lifecycle management
- Clinical validation of artificial intelligence and real-world performance
- Human oversight, accountability and transparency
Medical Data Science and Big Data
- Electronic health records and data warehouses
- Clinical data mining
- Big data analytics in healthcare
- Data quality, data integrity and missing data management
- Multi-source data integration
- Federated learning and privacy-preserving learning
- Real-world data and real-world evidence
Medical Imaging, Signal Processing and Multi-modal Artificial Intelligence
- Artificial intelligence in radiology, pathology and nuclear medicine
- Medical image classification, segmentation and reporting
- Multi-modal artificial intelligence models
- The integration of imaging, text, laboratory and clinical data
- Wearable device data and biosignal analysis
- Digital biomarkers
- Medical instrumentation and smart devices
Generative Artificial Intelligence and Large Language Models
- Clinical text generation and summarisation
- Automated discharge summaries, reports and consultation support
- Chatbots and virtual assistants in healthcare
- Reliability and hallucination management in large language models
- Prompt engineering and clinical applications
- Large local language models and privacy
- Artificial intelligence in education, research and patient communication
Health Information Systems and Digital Health
- Hospital information management systems
- Electronic health records
- e-Nabız, national health information systems and interoperability
- HL7, FHIR, DICOM and health data standards
- Mobile healthcare, telemedicine and remote patient monitoring
- Digital therapeutics
- Cybersecurity and data privacy in healthcare
Education, Simulation and Medical Informatics
- Artificial intelligence in medical education
- Virtual patient simulations
- Augmented reality, virtual reality and mixed reality applications
- Digital technologies in clinical skills training
- AI literacy for healthcare professionals
- Medical informatics curricula and competency frameworks
Ethics, Law and Social Impact
- The ethical dimensions of artificial intelligence in healthcare
- Patient privacy and data security
- Clinical responsibility and legal regulations
- Artificial intelligence and patients’ rights
- Health inequalities and the equitable use of technology
- Regulation, standards and certification processes
- Community health, public health and digital transformation
Types of Papers
Papers may be submitted to the conference in the following categories:
- Original research papers
- Application / system development notices
- Papers on clinical decision support and artificial intelligence applications
- Short statement
- Poster presentation
- Review / conceptual framework papers
- Student papers
- Papers on multidisciplinary project and field experience
Evaluation Criteria
Submitted papers will be assessed through a blind peer-review process. The following criteria will be taken into account during the assessment:
- The study’s contribution to the field of medical informatics
- Scientific originality and methodological soundness
- Feasibility from a clinical or healthcare system perspective
- Transparency of data, methods and results
- Ethical compliance and respect for patient privacy
- Explainability, reliability and bias management in artificial intelligence research
- The interpretability of the findings and their potential impact on healthcare
- Addressing technical, clinical, ethical and operational aspects together through a holistic AI approach
Prof Dr. Ahmet Yardımcı
Head of the Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University
Co-Chair of the 17th National Medical Informatics Congress
Prof Dr. Yeşim Şenol
Dean of the Faculty of Medicine at Akdeniz University
Co-Chair of the 17th National Medical Informatics Congress
