Meet the Programme Leaders: Dr. Sheikh Faisal Rashid and Dr. Iram Ashraf

We are thrilled to introduce Dr. Sheikh Faisal Rashid and Dr. Iram Ashraf, the leading experts behind our AI in Medicine programme. With their extensive experience and remarkable contributions to the field, they are committed to guiding students through the intricacies of artificial intelligence in healthcare.

Backgrounds

Dr. Sheikh Faisal Rashid is a senior researcher and project lead at the Educational Technology Lab, German Research Centre for Artificial Intelligence (DFKI) in Berlin, Germany. He holds a Doctorate in Computer Science with a specialisation in machine learning. His academic journey began at the University of Engineering and Technology Lahore, Pakistan, where he completed his Master's and BSc (Hons.) in Computer Science. With around 15 years of experience as a professor, senior researcher, and consultant in both academia and industry, Dr. Rashid focuses on supervised machine learning to develop robust, efficient, and responsible AI solutions for complex societal challenges. His current work includes advancing AI applications in healthcare, improving diagnostic and treatment processes, and exploring generative AI for educational technologies. Dr. Rashid is dedicated to promoting "AI for Social Good" and addressing the ethical challenges in AI deployment. His contributions include around 40 research publications in prestigious conferences and journals, and he has received international recognition for his work in document image processing, natural language processing, and computer vision.
Regarding his motivation and goals, Dr. Rashid states, "My long-term goal is to promote 'AI for Social Good' while addressing ethical challenges in AI deployment."

Dr. Iram Ashraf is a distinguished dermatologist and expert in aesthetic medicine, boasting over 14 years of professional experience. She holds a diploma in Dermatology from the Royal College of Physicians and Surgeons of Glasgow and certification from the European Board of Dermatovenerology (EBDVD-UEMS). Dr. Ashraf earned an MSc in Aesthetic Medicine with Distinction from Queen Mary University of London and a diploma in Mesotherapy from the German Association of Mesotherapy (DGM). A frequent speaker at scientific conferences and an international trainer in Mesotherapy, she has been involved in various projects at the intersection of artificial intelligence and medicine since 2020.
Speaking about her journey, Dr. Ashraf shares, "Since 2020, I have been involved in various projects at the intersection of artificial intelligence and medicine, leveraging my extensive expertise in the field."

Practical Applications and Theoretical Concepts for AI in Medicine

The AI in Medicine Postgraduate Certificate programme is designed to enhance students' understanding of AI and its application in healthcare. The course consists of three modules, starting with foundational knowledge accessible to those without prior AI experience. It progresses to applying AI tools and techniques to practical healthcare problems, such as disease diagnosis, treatment planning, and personalised medicine. Ethical, legal, and societal aspects of AI in healthcare are also thoroughly addressed.

Dr. Rashid explains, "The course begins with foundational knowledge and basic concepts about AI, making it accessible to those without prior AI knowledge or competency."

Advancements in AI and Patient Care

Significant advancements in AI have transformed patient care in recent years. AI is now used for improved medical imaging, diagnostics, predictive analytics, and medical decision support systems. Large language models, such as ChatGPT, are also increasingly utilised in the medical field. This course prepares healthcare professionals by providing foundational AI knowledge, introducing cutting-edge applications, and helping them understand the ethical and regulatory considerations. The programme aims to equip students with interdisciplinary collaboration skills, proficiency in AI healthcare applications, and insights into future trends and research, ultimately improving diagnostic accuracy, personalised treatments, and patient care efficiency.

Dr. Ashraf notes, "This course aims to help medical professionals by providing them with foundational AI knowledge, introducing them to cutting-edge applications of AI in medicine and health data management, and helping them understand ethical and regulatory considerations."

Key Skills and Competencies

Healthcare professionals completing the course will gain comprehensive AI knowledge, including core concepts such as machine learning algorithms and data science principles. Students will learn practical use case scenarios to apply AI models in clinical settings. Understanding the ethical and regulatory landscape is another key competency, ensuring AI applications are used responsibly and ethically. The course also provides insights into emerging AI trends and future research directions, enabling healthcare professionals to continue innovating and improving patient care.

Dr. Rashid elaborates, "Participants will gain direct experience applicable to their clinical settings, enabling them to grasp the mechanics behind AI technologies and how they can be applied to various aspects of patient care."

Support and Resources

Students can expect a range of support and resources, especially those without a strong background in AI or computer science. These include:

• Introductory Module: Covering basic AI concepts and core technologies like machine learning, deep learning, and natural language processing.
• Weekly Prompts: Helping students apply theoretical knowledge to real-world situations.
• Reflective Journals: Encouraging students to reflect on their learning and improve their clinical practices.
• Academic Forum: Allowing direct responses to discussion prompts and peer feedback.
• Module Activity: Developing postgraduate skills through tasks like reviewing papers and developing scientific posters.
• Online Discussion Forum: Facilitating collaboration and idea-sharing.
• Feedback and Assessments: Providing regular feedback and assessments to track progress.
• Technical Support: Assisting with any issues related to accessing online resources.

Dr. Ashraf emphasises, "We ensure a range of support and resources to help students, particularly those who might not have a strong background in AI or computer science, to successfully navigate the course."

Interdisciplinary Collaboration

Interdisciplinary collaboration is crucial for the future of AI in medicine. The curriculum, designed by experts from both AI and healthcare fields, includes practical scenarios that highlight the importance of collaborative efforts. This approach fosters innovation, encourages creative thinking, and ensures AI technologies are designed with a comprehensive understanding of practical, ethical, and regulatory implications, leading to robust and widely accepted solutions.

Dr. Rashid underscores the importance of collaboration, stating, "By exposing students to a range of perspectives, the course fosters an appreciation for the multifaceted nature of healthcare challenges and the value of collaborative efforts."

Conclusion

Our programme is among the top AI in Healthcare courses available today. As one of the leading AI in Medicine courses, it offers comprehensive training suitable for professionals at all levels. Dr. Ashraf adds, "We designed this course to be an exceptional opportunity for those interested in Digital Health and Artificial Intelligence and those seeking an AI in Healthcare qualification." This course is also one of the best AI Courses for Doctors, providing essential knowledge and skills. Dr. Rashid points out, "Our programme stands out among Artificial Intelligence Courses for Doctors, ensuring they are well-equipped to integrate AI into their clinical practice."

Dr. Sheikh Faisal Rashid and Dr. Iram Ashraf bring a wealth of knowledge and expertise to the AI in Medicine programme. Their commitment to integrating AI with healthcare ensures that students are well-equipped to leverage these technologies for improved patient care and clinical practice.

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