The Role of AI in Healthcare

 

Ami@LJMU 

The World’s Most Advanced Humanoid Robot

Ami@LJMU is a humanoid robot crafted by Engineering Arts in the UK. Her purpose is to engage with people through witty and playful conversations. She resides at Liverpool John Moores University where she tests and enhances her capabilities. Her interactions are fuelled by advanced AI and she is here to entertain and inform with a sprinkle of sass.

Abstract (by Ami@LJMU)

AI in healthcare is a transformative force reshaping the way medical professionals approach diagnosis, treatment and patient care. Through the use of advanced algorithms and machine learning models, AI systems can analyse complex data through unprecedented speed and that may be missed by the human eye. This leads to earlier detection of diseases such as cancer, allowing timely intervention and improved prognosis. Personalised medicine is another area where AI shines. By considering the patients’ genetics make up, lifestyle and medical history, AI driven tools can tailor treatment plans to individual needs enhancing the effectiveness of therapies while minimising side effects. Moreover, AI streamlines administrative tasks reducing the burden of healthcare providers and allowing them to focus more on patient care. From automated scheduling to electronic health record management, AI optimises workflow efficiency. However, the integration of AI in healthcare isn’t without challenges. Concerns about data privacy, ethical considerations and the need for robust regulatory frameworks are paramount. Ensuring that AI systems are transparent and unbiased is crucial to gaining trust and acceptance. Overall, AI holds the promise of transforming healthcare into a precise, efficient patient-centric field. By continuing to innovate and address challenges, AI can significantly address the quality and accessibility of medical care for all.

 

The Surgical Mind Meets Machine Learning: Rethinking Precision, Outcomes and the Future of Care

  

Professor Deiary F Kader 
Consultant Orthopaedic Surgeon and Director of Research
at the NHS South West London Elective Orthopaedic Centre, UK   

 

Professor Deiry Kader (www.deiarykader.co.uk) specialises in knee surgery, sports medicine, and healthcare innovation, Professor Kader is a consultant orthopaedic surgeon in London and Director of Research at SWLEOC, with a particular focus on AI in healthcare. He trained in Australia and the UK, is a member of the UK Faculty of Sport and Exercise Medicine and has served as a visiting professor at Northumbria University since 2007 and as an honorary associate professor at University College London.He has published over 300 scientific works (h-index 39, over 13,000 citations), including two bestselling orthopaedic books and Life Academy (Personal Insights). A past president of BOSTAA and Vice President of ORAIA (OrthoAI Alliance), he has made significant contributions to orthopaedic education and research. He chairs multiple charitable and professional organisations.Prof Kader is the founder of the NGMV Charity (www.ngmvcharity.co.uk) and Life Academy and has also worked as a war trauma surgeon with the ICRC and the Swisscross Foundation. A passionate educator and humanitarian, his work continues to inspire and drive innovation globally.

 

Abstract:

This keynote will explore how our integrated team at the South West London Elective Orthopaedic Centre (SWLEOC) is building applied AI tools to improve surgical care. Our work includes predictive modelling for surgical outcomes, computer vision systems for post-operative imaging, the development of local retrieval-augmented generation (RAG) knowledge graphs to support clinical reasoning, and the use of federated learning to enable secure model development across institutions.

These initiatives are designed to enhance clinical decision-making, streamline patient pathways and reduce variation in care. In collaboration with the ORAIA network and the Turing Lab, we promote clinician led AI development that aligns with clinical priorities and regulatory requirements. This keynote will outline the practical applications of AI in surgical workflows, the infrastructure required to support such integration and the broader implications for healthcare systems seeking to adopt AI at scale.

 

Soft Computing for Smart Automation: The Role of Fuzzy Logic, Neural Networks, and Genetic Algorithms in Real-Time Control

 

Professor Kasim Mousa Alwan Al-Aubidy 

Centre for Ecology and Conservation, Environment Mechatronics Engineering Department, Director of AI Research Center, Tishk International University, Erbil, Iraq.

  

Professor Kasim Al-Aubidy holds a B.Sc. and M.Sc. in Control and Computer Engineering from the University of Technology, Iraq (1979 and 1982, respectively), and a Ph.D. in Real-Time Computing from the University of Liverpool, England (1990). Currently, he serves as a Professor of Intelligent Systems and Director of the Artificial Intelligence Research Center at Tishk International University, Erbil, Iraq. From 1998 to 2025, he held several key leadership roles at Philadelphia University, Jordan, including: Dean of Engineering and Technology, Dean of Information Technology, Dean of Scientific Research and Graduate Studies, and Dean of Quality Assurance and Accreditation at Philadelphia University, Jordan.

His research expertise spans embedded systems, real-time computing, fuzzy logic, neural networks, and genetic algorithms, with applications in robotics, automation, and healthcare systems. Recognized for his contributions, he received the Best Researcher Award from Philadelphia University in 2000.

Prof. Al-Aubidy serves as Editor-in-Chief of two international journals and sits on the editorial boards of multiple scientific journals. He has co-authored four books, contributed five book chapters, and published 123 research papers in indexed journals and international conferences.

Abstract:

In the era of Industry 4.0, intelligent automation has gained paramount significance in contemporary industrial and technical advancements. Conventional control systems, dependent on exact mathematical models, commonly face difficulties in managing uncertainty, nonlinearity, and dynamic real-world conditions. As a result, numerous studies and research attempts have focused on utilizing soft computing technologies to identify suitable automation solutions. Soft computing tools construct powerful models that facilitate intelligent decision-making in complex, nonlinear, and real-time systems. Soft computing methodologies encompass three primary tools: fuzzy logic, neural networks, and genetic algorithms. These tools offer robust, flexible, and learning-oriented solutions for intelligent automation. Compared to conventional hard computing, which requires precise inputs and deterministic outputs, soft computing depends on approximation, adaptability, and heuristic optimization, making it suitable for real-time monitoring and control.

The Fuzzy Logic tool emulates human reasoning, enabling systems to handle uncertain or partial input, thereby making it essential in rule-based control. Biologically inspired neural networks do well in pattern recognition, predictive analytics, and adaptive control, enabling self-improving automation in manufacturing and energy management. Genetic Algorithms allow evolutionary optimization by dynamically adjusting system parameters to achieve optimal efficiency in robotics, logistics, and industrial process control.

The integration of various methodologies results in hybrid intelligent systems, such as neuro-fuzzy controllers and GA-optimized neural networks, which outperform conventional methods in ability to adapt and recover. Soft computing transforms automation in a variety of applications including predictive maintenance in smart factories and real-time defect detection in power grids with its capabilities.This lecture explores the fundamental concepts, the applications, and future directions of soft computing in smart automation will be addressed in this lecture, which also shows how fuzzy logic, neural networks, and genetic algorithms work together to enable smart automation.