Welcome to AI4Me'2023!

The emergence of artificial intelligence (AI) in medicine has been groundbreaking, reshaping the way we diagnose, treat and monitor patients. AI offers a real opportunity in medicine, not only to automate some of the problem-solving carried out by doctors and other medical professionals, but also to make quicker and better decisions, enabling more personalized treatments and apply problem-solving techniques that humans alone could not. However, there remain many barriers to wide-scale implementation of artificial intelligence tools, including our historic practices of collecting and documenting patient data, as well as the organization of our health care system. Lack of training has Health care providers underprepared to face the full potential of these tools and safeguard against adverse consequences for patient care. Given the exciting opportunities for the use of artificial intelligence in medicine, ways to overcome associated challenges. This scientific day will be an opportunity for researchers and other healthcare and AI experts to discuss and explore the current state of AI literacy among Health Sciences educators, health care professionals and how to introduce the students to personalized learning and adaptive learning and preparing them for the future work place with AI technology implementation. The intended audience for this event includes AI researchers, as well as clinicians and medical researchers and practitioners who are interested in exploring the intersection of AI and medicine.


Keynote Speakers


Christos Davatzikos
  • Director, Center for Biomedical Image Computing and Analytics (CBICA)
  • Director, Artificial Intelligence in Biomedical Imaging Lab (AIBIL)
  • Joint Affiliations: Bioengineering and Applied Math graduate groups
  • University of Pennsylvania, Philadelphia, USA


Aouiche Chaima
  • Tebessa, ALGERIA
  • Lamis Laboratory
  • University of Larbi Tebessi,Tebessa,Algeria
Pr. Christos Davatzikos is the Wallace T. Miller Sr. Professor of Radiology at the University of Pennsylvania, and Director of the Center for Biomedical Image Computing and Analytics. He holds a secondary appointment in Electrical and Systems Engineering at Penn as well as at the Bioengineering an Applied Mathematics graduate groups. Dr. Davatzikos’s interests are in medical image analysis. He oversees a diverse research program ranging from basic problems of imaging pattern analysis and machine learning, to a variety of clinical studies of aging and Alzheimer’s Disease, schizophrenia, brain cancer, and brain development. Dr. Davatzikos has served on a variety of scientific journal editorial boards and grant review committees. He is an IEEE fellow, and a fellow of the American Institute for Medical and Biological Engineering.
Title : Machine learning methods for understanding heterogeneity of neurologic and neuropsychiatric diseases
Dr. Aouiche Chaima, Ph.D. received her bachelor and Master degrees in computer science from Larbi Tebessi University, Tebessa, Algeria, in 2011, 2013, respectively and Ph.D. degree in computer science from Northwestern Polytechnical University, Xi’an, China, in 2021. She joined key laboratory of big data storage and management as a researcher in 2014. Since September 2022, she has been with the Faculty of science and technology, Larbi Tebessi University, Algeria, where she is currently an assistant Professor. Her research interests include data mining, bioinformatics, big data and machine learning. Dr. Chaima has authored/co‐authored many publications in various high impact factor, peer‐reviewed, journals and international conferences.
Title : Predicting Cancer-related Genes from Integrated Data Sets

Panel Discussions

Title : Data collection and preparation

Moderators :Dr. Chawki Djeddi & Dr. Issam Bendib

Title : Approaches and tools for artificial intelligence in Medicine

Moderators : Dr. Lakhdar Laimeche & Dr. Gasmi Mohamed
General Chair :
Pr. Mohamed Amroune
Scientific Chair :
Dr. Issam Bendib
Organizing committee Chairs :
Dr. Gasmi Mohamed
Dr. Khediri Abderrazek