The IEEE Jordan AI, Machine Learning, Deep Learning, Computer Vision, and LLM Group is a specialized community focused on advancing knowledge and fostering innovation in artificial intelligence and its subfields. Through workshops, discussions, and collaborative projects, the group empowers enthusiasts and professionals to explore cutting-edge technologies, share expertise, and contribute to AI-driven solutions that address real-world challenges.
Upcoming Masterclasses
1- Deep Learning for Biomedical Signal Processing 4th January 2025 – 17:00 (+3 GMT)
About Speaker:
Professor Awad Al-Zaben is a distinguished faculty member in the Biomedical Systems and Medical Informatics Department at Yarmouk University. Holding master’s and doctoral degrees from Colorado State University, USA. His research expertise include biomedical signal processing, pattern recognition, and classification; medical electronics and instrumentation; and biomedical modeling. He has contributed significantly to the field with numerous journal publications and two patents: one for impedance analysis of esophageal maladies and another for esophageal waveform analysis for detecting and quantifying reflux episodes. A Senior Member of the IEEE and co-founder of the IEEE EMBS Jordan Chapter. Professor Al-Zaben’s achievements have been recognized with several awards, including the Philadelphia University Award for best patent (2016) and the Hisham Hijjawi Academic Distinction Awards for both teaching and scientific research (2005).
The lecture will cover the basics of machine learning with applications in biomedical signal processing. Topics covered in the lecture include:
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Biomedical Signals
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Machine Learning Stages
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Neural Network (NN) Architectures and Other Machine Learning Architectures
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Deep Learning
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Biomedical Signal Processing Application Examples”
To be added as soon as possible
To be added as soon as possible
Previous Masterclasses
1- Leveraging AI in Medical Education & Health Care – 7th December 2024
About Speaker:
Dr. Mona Hmoud AlSheikh
MBBS, PhD physiology, MHPE, FF, Academic Accreditation and Assessment , Keele University, Diploma AI.
Associate Professor
Head of the Research and Innovation Unit, Imam Abdulrahman Bin Faisal University (IAU)
Vice-president of Saudi Society for Medical Education
Artificial intelligence (AI) has significantly transformed medical education and healthcare delivery by introducing innovative tools and systems that enhance learning, assessment, and clinical decision-making. In medical education, AI-driven intelligent tutoring systems provide personalized feedback, adaptive testing, and simulation-based training, allowing students to develop clinical reasoning, procedural skills, and communication competencies. Applications such as virtual patient simulations, surgical skill evaluations, and AI-generated progress tracking have revolutionized practical skills training, fostering continuous improvement and competency.
In healthcare, AI technologies such as machine learning algorithms and large language models (LLMs) are increasingly applied in diagnostics and treatment planning. AI enables the integration and analysis of large datasets, improving diagnostic accuracy and optimizing patient outcomes. Despite its potential, challenges such as bias, lack of transparency in algorithms, and ethical concerns regarding privacy and accountability remain significant barriers to widespread adoption.
This study aims to explore the multifaceted applications of AI in medical education and healthcare, highlighting its benefits, limitations, and future directions. By examining current AI-driven interventions and their impact, this research seeks to inform strategies for effective integration into education and clinical practice, ensuring that these technologies complement human expertise rather than replace it