First International Conference
on AI in Medicine and Healthcare
(AiMH' 2025)

Topics of Interest include, but not limited to:​

• AI in Clinical Decision Support
• AI in Medical Imaging and Diagnostics
• AI in Predictive Analytics and Population Health
• AI in Drug Discovery and Development
• AI in Genomics
• AI in Patient Care and Personalized Medicine
• AI for Health Informatics and Data Science
• AI-driven Telemedicine and Intelligent Healthcare
• Ethics and Governance of AI in Healthcare
• AI in Medical Education and Training.

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Special Session:

AI in Medical Imaging for the Early Detection of Major
Non-Communicable Diseases

The primary aim of this session is to discuss major AI developments in the field of medical imaging for six different radiological sub-specialties. Papers would cover AI advances in the areas of thoracic, cardiac, breast, liver, neuro, and musculoskeletal imaging, with a focus on implementation of AI software in clinical radiological practice for the early detection of non-communicable disease which are leading causes of mortality worldwide.

• AI in Thoracic Imaging

The papers should cover original researches on AI software implementation in lung cancer screening settings to reduce radiologist workload. Lung cancer screening is essential for the early detection of lung cancer which remains the leading cause of cancer-related mortality. AI is necessary in this field to overcome the major challenge of the global radiologist workforce shortfall which stands to hinder the implementation of large-scale lung cancer screening programs.

• AI in Cardiac Imaging

The papers should cover original researches on AI coronary artery calcium (CAC) detection and classification and the implications for implementation into clinical practice for the early detection of coronary artery disease, a leading cause of mortality worldwide.

• AI in Breast Imaging

The paper should cover reviews of the integration of AI into breast cancer screening for the reading of mammograms. Current European clinical practice guidelines dictate two radiologists perform and independent read of all mammograms performed, followed by a third arbitration read by a third senior radiologist for any discrepancies. AI shows potential to replace either one radiologist or perform a standalone read without reducing cancer detection accuracy, meaning a substantial reduction in radiologist workload could be achieved.

• AI in Liver Imaging

The papers should cover reviews on applications of AI software for improving diagnostic accuracy and reducing invasive procedures for the detection of liver diseases.

• AI in Neuro Imaging

The papers should cover reviews on the use of AI software to enhance radiologist performance and interpretation time of non-enhanced CT scans for the assessment and characterization of early ischemic brain tissue injury seen in ischemic stroke patients. Also, although in earlier stages of development, AI shows promise for detection of intercranial hemorrhage, which would help enable triage of cases requiring immediate review by a radiologist.

• AI in Musculoskeletal Imaging

The papers should cover reviews on AI applications in MSK imaging detailing where AI could assist radiologists to optimize their workflow for fracture detection and classification, bone age estimation, osteoarthritis, and bone-soft tissue tumors.

Session Chairman:

Mr. Harriet Lancaster,

Institute for Diagnostic Accuracy,

Groningen, The Netherlands

e-mail: lancaster@i-dna.org

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
• Special publishing theme within conference proceedings