Alessandro Ruggiero
University of Salerno (Italy)

Biotribology in arthroplasty: toward the accurate in-silico wear prediction

Nowadays, arthroplasty is one of the most successful orthopedic surgical procedures, although it involves challenges to overcome. The patients undergoing total arthroplasty now includes younger and more active ones who require a broad range of motion and a longer service lifetime for the replaced joints. Wear is still one of the main issues affecting joint prostheses endurance, causing loosening and, eventually, implants failure. Actual in vitro wear tests (simulators) have a long duration, are very expensive and does not take into account all the possible daily activities of the patients; thus, the challenge to obtain a complete in silico tribological and dynamical model of the (bio)tribo-systems could give the possibility to overcome the actual testing procedures and could contribute as tool for a more and more accurate tribological design of human prostheses.

The talk is devoted to give an overview of the last research results toward this aim, underlining some open problems in contact mechanics, numerical stress-strain analysis, musculoskeletal multibody modeling, synovial lubrication modeling (boundary/mixed, hydro-dynamic and EHD), with the aim to establish future research cooperation with the colleagues attending BIOMDLORE 2020.

Alessandro Ruggiero is an Associate Professor, qualified as a Full Professor in 2017, at the Department of Industrial Engineering, University of Salerno (Italy). He attended a PhD course in Tribology at the University of Pisa (Italy) in 1997–1999. To date, he authored more than 180 scientific papers in indexed international journals and national and international proceedings. He serves as a referee, editor and member of the editorial board for many prestigious international journals. His current research interests are focused on (bio)tribology, dynamics of mechanical systems, noise and vibration control.

Adel S. Elmaghraby
University of Louisville (USA)

Artificial intelligence solutions for health and wellness

The recent advances in Artificial Intelligence (AI) including the use of data science and techniques such as deep learning are having a great impact on Healthcare and understanding of wellness. The use of AI as related to Healthcare will be discussed in the context of Health 4.0. Examples include applications to predictive analytics for patient care, medical image analysis and annotation, document and social media text analysis.  This work is part of a larger project which integrates a variety of information sources from clinical data, social media, and professional literature to better guide our understanding of health and wellness. The AI techniques used include Deep Learning, NLP and ANN, and applied to doctors’ annotation and public sentiment combined with medical literature. Imaging work has significantly reduced the effort of medical professionals to allow them to focus on the patient. We shall also discuss emerging topics as they relate to e-health, such as Industry 4.0, Precision Medicine, Mobile Health, 5G, Big Data, and Cyber-Physical Systems.

Adel S. Elmaghraby is the Director of Industrial Research and Innovation, and Winnia Professor of Computer Science and Engineering at the Speed School of Engineering, University of Louisville (USA). He has also held appointments at the Software Engineering Institute, Carnegie Mellon University, and the University of Wisconsin-Madison. He advised over 60 master’s and 27 doctoral graduates. His research contributions and consulting spans the areas of Intelligent Multimedia Systems, Artificial Intelligence, HPC, Cybersecurity, Visualization, and Simulation. His research applications include Smart Cities, Data Analytics, Medical Imaging, Bioinformatics, and Computer-Aided Diagnostics. He is a well-published author, public speaker, member of editorial boards, and technical reviewer. He was recognized for his achievements by several professional organizations including a Golden Core Charter Membership by the IEEE Computer Society at the 50th anniversary celebration. Adel S. Elmaghraby continued collaborations, mentoring, and scientific contributions have resulted in research funding, international collaboration, and published articles in many prestigious journals such as IEEE-TMI, Medical Physics, Journal of Neuroscience Methods, and Protein Engineering. He is Life Senior Member of IEEE, the former President and Lifetime Member of the Association of Egyptian American Scholars.