AIiH aims to provide a prominent platform for researchers and practitioners who are devoted to improving healthcare using modern artificial intelligence. We recognise that healthcare applications present complex and sometimes unique challenges across a wide spectrum, from ethics to technical developments, that generic AI methods are often inadequate. By creating this dedicated forum, we encourage discussions and disseminations of efficient and effective AI solutions and technologies for healthcare, and in turn we hope to influence the research, technology adoption, and decision making in healthcare.
Authors are invited to submit full-length high-quality papers in both theory and/or application areas that are closely relevant to the conference. Submitted papers will be refereed on their originality, presentation, empirical results, and quality of evaluation.
All full papers will be reviewed “doubly blind“, normally by three members of our international programme committee. Please note that AIiH is a single track conference with oral and poster presentations and will include a number of keynote presentations. Accepted full papers will be included the conference proceedings.
AIiH also welcomes short abstract submissions to be included as poster or short spot-light presentation at the conference. This is to both enable fast dissemination of promising preliminary findings and to encourage attendance by a broader audience of early career researchers (including research students), healthcare professionals, and industrial practitioners. Abstracts will be archived, with DOIs, on zenodo.org
Submissions for special sessions are also welcomed. Special session can contain both full papers and abstracts. Full papers are reviewed in the same way as those submitted to the main sessions (double blind review and the same page limit) and are included in the conference proceedings. Absracts are archived online with DOIs. Oral presentation with abstract submission is possible if highly recommended by the session organisers.
The conference welcomes submissions of novel research work in the following areas, but not limited to:
- Ethics of AI in Healthcare
- Predictive Analytics in Healthcare
- AI driven proactive care and predictive intervention
- AI driven early diagnosis and prevention
- Machine and deep learning approaches for health data
- AI-aided medical signal processing
- AI-aided medical imaging (CT, MRI, ultrasound, histopathology, etc.)
- Medical image analysis and processing
- Digital and virtual pathology / neurology
- AI in Pharmacology: drug discovery and drug development
- AI driven Digital Twinning in Oncology/Medicine
- Precision Medicine and AI
- AI for drug screening and discovery
- AI led personalised healthcare
- AI-aided large-scale cohort data analyses
- Patient-centred AI design
- Assisted living technology
- Healthcare workflow optimisation and automation
- AI driven robotics for healthcare
- AI in mental health
- Patient data and privacy
- AI in proactive health management