About the Event

Artificial intelligence is rapidly transforming medicine and healthcare, moving from experimental applications towards clinically integrated systems that support prevention, diagnosis, treatment, rehabilitation and long-term patient care. AiMH’ 2027 will provide an international forum for presenting and discussing the latest scientific advances, technological developments and practical applications of AI across the healthcare ecosystem.

The conference will place particular emphasis on multimodal and generative AI, medical foundation models, large language and vision-language models, clinical AI agents, intelligent decision-support systems and AI-assisted robotics. These technologies offer new opportunities to combine medical images, electronic health records, biosignals, genomic data, laboratory results and patient-generated information to enable earlier diagnosis, more precise treatment and increasingly personalized care.

AiMH’ 2027 will focus not only on algorithmic performance, but also on the translation of AI research into safe, effective and clinically meaningful solutions. The programme will address real-world validation, prospective clinical studies, interoperability with healthcare information systems, human–AI collaboration, usability, workflow integration, post-deployment monitoring and the assessment of measurable benefits for patients, healthcare professionals and health systems.

Special attention will be given to trustworthy and responsible medical AI. Key challenges include model bias and health inequalities, hallucinations and unreliable outputs, explainability, uncertainty estimation, patient privacy, cybersecurity, data ownership and governance, accountability and regulatory compliance. The conference will encourage research into privacy-preserving and federated learning, synthetic health data, robust and generalizable models, continuous performance monitoring and effective human oversight.

The scope of AiMH’ 2027 also extends to AI-enabled telemedicine, wearable and implantable devices, remote patient monitoring, digital therapeutics, population health, hospital operations, medical education, drug discovery and clinical trials. Particular interest will be given to scalable and resource-efficient solutions that can improve access to high-quality healthcare in remote, underserved and low-resource regions.

By bringing together researchers, clinicians, engineers, data scientists, healthcare providers, industry representatives, regulators and policymakers, AiMH’ 2027 aims to strengthen interdisciplinary cooperation and accelerate the responsible adoption of AI in medicine. The conference welcomes theoretical studies, methodological advances, clinical investigations, implementation reports, systematic evaluations and case studies demonstrating both successful applications and lessons learned.

The 3rd International Conference on AI in Medicine and Healthcare will be co-located with the 9th International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2027) under the same conference umbrella. Both events are organized by IFSA, a non-profit professional association serving academia and industry since 1999. The programme will include plenary and invited talks, contributed oral and poster presentations, as well as social and cultural activities supporting professional networking and international collaboration.


Call for Papers

Topics of Interest include, but not limited to:​

* AI in Clinical Decision Support and Risk Stratification
* AI in Medical Imaging, Radiology, Pathology and Diagnostics
* AI in Predictive Analytics, Preventive Medicine and Population Health
* AI in Precision Medicine and Personalized Treatment
* AI in Drug Discovery, Repurposing and Development
* AI in Clinical Trials and Real-World Evidence
* AI in Genomics, Proteomics and Multi-Omics
* AI in Surgery, Medical Robotics and Interventional Medicine
* AI in Rehabilitation, Assistive Technologies and Healthy Ageing
* AI in Mental and Behavioral Health
* AI in Patient Engagement, Virtual Assistants and Digital Therapeutics
* AI-enabled Telemedicine and Remote Healthcare​​
* Ethics and Governance of AI in Healthcare
* AI in Medical Education and Training


Special Session:

Artificial Intelligence for Predictive Analytics in Digital Health:
Applications in Critical Care and Intensive Care Medicine

The goal of this special session is to bring together academics, medical experts, healthcare practitioners, technology developers, and industry representatives to discuss the latest developments and innovative approaches in AI-based predictive analytics for medical care. Particular attention will be given to health-related technologies, with a special focus on intensive care and emergency medicine. The session also aims to attract empirical research papers, industrial applications and case studies, comparative studies, review papers, and other innovative contributions that address current challenges and propose new solutions in the field of intelligent healthcare.


Topic of Interest:

• AI-based prediction models in monitoring ICU patients
• Early warning systems for sepsis, septic shock, and multiple organ failure
• Mortality prediction through machine and deep learning
• AI-assisted risk evaluation in emergency or intensive care
• AI-controlled ventilation and respiration management
• Predictive analytics through electronic health records (EHR)
• AI for personalized medicine in emergency care
• Reinforcement learning for therapeutic optimization
• Federated learning for collaborative health analytics
• Remote patient monitoring through wearable and IoMT devices
• Multimodal AI technology providing imaging, clinical, and lab information
• Natural language processing for ICU clinical notes
• AI optimization of inventory procedure in ICUs
• Recommendation systems for personalized treatment
• AI usage in tele-ICU services
• Decision support systems in an emergency
• The role of digital biomarkers and continuous health status monitoring
• Privacy-preserving AI in healthcare system and secure data sharing
• Large Language Models for intensive care decision-making
• Generative AI in digital healthcare • Human-centered AI in intensive care


Session Chairman:

Prof., Dr Soobia Saeed,
Taylor's University, Malaysia


Special Sessions:

Authors are welcome to organize and manage special sessions during the conference. Each session must contain 4-6 papers in a related field as specified above.

Session organizers will get: ​

* Certificate of appreciation
* Free registration for the event