Advances in AI and ML for Healthcare and Medicine

 

This special session is organised and supported by  the following educational partner

  • The University of Anbar , Ramadi-Iraq 

Session Chair:

  • TBC

Session Co-Chair:

Synopsis:

Artificial Intelligence (AI) and Machine Learning (ML) has innumerous applications in healthcare and medicine. AI enables us to imagine improved methods of delivering care and handling modern healthcare challenges while machine-learning empowered applications performing tasks that are typically done by workers but in shorter time and lower cost. In fact, advances of data collection means, and methods lead to a large-scale healthcare data that can be used to derive better information as a breakthrough toward more advanced computational reasoning approaches that support human decision-making. Proper machine learning algorithms trained on gold-standard healthcare data will soon be routine to see everywhere in healthcare and medicine, from screening through to diagnosis, treatment, and population health. Further to this, we can derive new solutions to handle global pandemics, exploit patterns in large-scale healthcare data or medical images, developing explainable AI models, and monitoring and tracking patients.

Topics:

In this special session, we are targeting state-of-the-art as well as emerging topics pertaining to AI and machine-learning and the effective strategies for their implementation to improve our healthcare system. We aim to provide an opportunity for Researchers, Academicians, Industry persons and students to present their works, share knowledge, and provide insights into intelligent and innovative applications. The areas of interest include (but are not limited to):

  1. Applications of AI and ML in healthcare and medicine.
  2. Explainable AI in healthcare and medicine.
  3. Evolutionary computation and neural networks.
  4. Deep learning and big healthcare data analytics.
  5. AI empowered medical imaging technologies.
  6. Robots and sensing technology in healthcare.
  7. Health misinformation on social media.Healthcare data management and processing.
  8. Biomedical intelligence and computational genomics.

Paper Submission:

Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.