This workshop focuses on the advanced applications of MRI sequences in brain tumour diagnosis, emphasising the enhancement of diagnostic accuracy through techniques such as DWI, PWI, SWI, and MRS. Participants will gain insights into the physio-anatomical information these sequences provide, alongside an introduction to AI machine learning algorithms and their role in improving diagnostic outcomes. The workshop includes hands-on, group-based analysis of actual case studies under the guidance of a senior consultant neuroradiologist. Attendees will explore the challenges of AI implementation, ethical considerations, and develop both theoretical and practical skills in assessing AI-based versus human radiologist performance in diagnosing brain tumours.
After attending and actively participating in this CPD Course/Workshop, attendees are anticipated to attain the following Course Learning Outcomes (CLOs):
CLO1: Gained insightful knowledge of advanced MRI sequences (such as DWI, PWI, SWI, and MRS) used for brain tumor diagnosis.
CLO2: Developed critical understanding of physio-anatomical information based on advanced MRI sequences and their role in enhancing the brain tumors’ diagnosis process and its outcomes.
CLO3: Explored advanced AI machine learning algorithms applied using advanced MRI sequences of brain tumors.
CLO4: Gained insightful hands-on, group-based analysis and diagnosis of brain tumors using actual case studies based on advanced MRI sequences with thorough group-based presentation and full guidance by a senior consultant neuroradiologist.
CLO5: Explored the potential challenges and effectiveness of applying AI machine learning algorithms using advanced MRI brain sequences in yielding accurate and qualitative brain tumors diagnosis.
CLO6: Gained insights into ethical issues in relation to the advanced applications of AI machine learning algorithms using advanced MRI sequences for brain tumor diagnosis.
FULLY In Person (NOT ONLINE) Interactive, Group-Basd Settimngs, Case-Based, Problem-Based and Scientifically Evidenced-Based.
Staff & Learners involved in the Neuro Patient Journey and in particular:
· Medical professionals (radiologists, oncologists, radiographers).
· Biomedical Engineers.
· Data scientists and AI practitioners.
· Researchers in medical imaging and oncology.
· Graduate and postgraduate students in related fields.
Our education environment is a melting point of cultures and backgrounds. From our multidisciplinary community of tutors and workshop tuees attending this digitally transforming healthcare care workshop, you'll find a welcoming, scientific, technical, practical, digital tooling, and inclusive environment at Global Academy for Digital Health (GA4DH).
June 5, 2025, 9am - 6pm
Certificate of the Global Academy for Digital Health
Our faculty are experts in their fields, dedicated to helping you excel in your continuing professional in digital health transformation. Get to know our amazing professors and tutors who will be teaching you at Global Academy for Digital Health (GA4DH):
النظامية العالمية للبحث والتطوير في العلوم الطبية والطبيعية والهندسية
9th Floor
Iskan Housing Compound
Amman – Jordan
Special Introductory Fees
Healthcare Staff: JD350 now JD100
Students in Current Education: JD200 now JD65
Ready to take the next step in your continuing professional development in this area of interest? Apply NOW to Global Academy for Digital Health (GA4DH) and start your journey toward a brighter digital health transformation journey. Click the link below and fill yin your details to receive instructions for joining.
20+ years' experience. Gained fellowship from Cleveland Clinic, USA. Consultant Neuro radiologist in ministry of health, X head of Oncology Center Queen Alia Hospital, Consultant Neuro Radiologist in KHMC and head of Radiology development in different private hospitals, Over 20 Published papers in Radiology in index journals, research Interests: MS, brain tumors advanced images, MRI and CT cisternography for CSF leak.
She has expertise in medical imaging, image processing, and automation algorithms. She is more focused on MRI including Perfusion MRI, Functional MRI, Susceptibility MRI, and other advanced techniques. She is the author of several notable research works, including some recently published works “Automated Multi-Class High-Grade Glioma Segmentation Based on T1Gd and FLAIR Images”, “Electrical Impedance Tomography Image Reconstruction for lung monitoring based on Ensemble Learning Algorithms”, “Leukemia classification using different CNN-based algorithms-comparative study”.
Professor of Digital Health, President of the Global Academy for Digital Health, Bristol, UK; KHCC Professor of Cancer Care Informatics, King Hussain Cancer Center 2018-2024 with secondment from University of West of England, Bristol; 1st Professor Awarded the title of “Professor in Cancer Care Informatics”; Co-founder and Co-director of the 1st International MSc Cancer Care Informatics programme hosted by King Hussain Cancer Center, with the joint degree awarding by the University of Jordan and King Hussain Cancer Center; Founder and Chair of the Global Digital Health Conference, Knowledge Exchange and Empowerment, gDigiHealth.KEE 2024 Conference; Co-General Chair of the gDigiHealth.KEE 2024 Conference, September 24-26, 2024; Founder of the iPeople.wd Data Analytics for People with disabilities platform; Founder and Director of the iPeople.wd.SLH Data Analytics Platform for Speech, Language and Hearing Disorder, with the first instance in Jordan jointly signed initiative & MoU the Higher Council for the Rights of People with Disabilities (HCD) in Jordan: iPeople.wd.SLH.Jordan; Supervised 20+ PhD students to successful completion; Has over 140 journal and conference, and book chapters; Has been referee on scientific committees and panels for the promotion of academic staff; Has been referee on Councils for Awarding International Prizes for Scientists and Scholars; Invited keynote speaker several global leading conferences.