Call For Papers
The era of digitized healthcare is transforming rapidly, with intelligent and secure health informatics systems at the heart of this revolution. As artificial intelligence, machine learning, cybersecurity, and digital health technologies continue to advance, their integration into healthcare environments is becoming essential — not only for researchers and innovators but also for start-ups and enterprises aiming to build a smarter, patient-centred future. The need for secure, scalable, and intelligent solutions is driving innovation across hospitals, clinics, public health agencies, and personal health technologies. Recognizing this importance, the International Symposium on Intelligent and Secure Health Informatics Systems (IS-HIS 2025) invites researchers, practitioners, and industry experts to submit original, unpublished work that advances the field of health informatics with a strong focus on intelligence and security. This Symposium aims to explore the latest advancements in artificial intelligence, machine learning, and cybersecurity applied to health informatics systems, enhancing patient care, data security, operational efficiency, and shaping the future of healthcare delivery.
Topics of Interest
We welcome submissions on a wide range of topics, including but not limited to
- Machine learning applications in healthcare
- Deep learning for medical image analysis
- Natural language processing for electronic health records​
- Genomic and multi-omics data integration for personalized treatment strategies
- Digital twins in healthcare for simulating and predicting health outcomes
- Lifestyle and behavioral data analysis for individualized health interventions​
- Smart healthcare infrastructure
- IoT and wearable device integration
- Real-time health monitoring systems​
- Sensor design and integration for wearable and implantable devices
- Secure data transmission protocols for BSNs
- Real-time health monitoring applications using BSNs​
- Data encryption and privacy-preserving techniques
- Blockchain applications in health data management
- Access control and authentication mechanisms​
- Machine learning models for target identification and compound screening
- AI-enhanced clinical trial design, recruitment, and real-time monitoring
- Post-market surveillance and pharmacovigilance through data mining
- AI-assisted clinical documentation and decision support for nurses
- Predictive analytics for patient deterioration and staffing allocation
- Virtual simulation and AI-driven training for nursing education
- Big data analytics in healthcare
- Predictive modeling for disease outbreaks
- Data visualization techniques for health informatics​
- Automated image analysis and pattern recognition in pathology
- AI-integrated laboratory information systems (LIS) for workflow efficiency
- Predictive maintenance and quality control in lab equipment using AI
- AI-driven patient flow optimization and resource management in hospitals
- Smart scheduling systems and virtual health assistants
- Population health management through AI-based data aggregation and insights
- Deep learning for radiology, pathology, and multi-modal diagnostic support
- Personalized treatment planning using predictive and prescriptive analytics
- Clinical decision support systems (CDSS) for complex case management