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This MOOC will allow healthcare workers and other non-technical professionals interested in AI applications in healthcare to participate in the conversation about AI and health. For the first time, non-technical professionals will be empowered to develop AI-related projects to enhance and elevate their practice.
AI continues to contribute to progress against leading causes of disease and death whether through sharing data and information about clinical trials in real-time or using AI to develop new insights into the diagnosis and treatment of diseases. Specific applications include improving patient care through machine learning and data analysis, fast and accurate diagnosis, precision in treatment planning, medical imaging, and patient data analysis.
Professionals who work in non-technical roles in healthcare also need foundational knowledge and practical insights to help them take advantage of AI. Objectives here range from the safe and ethical application of AI in clinical settings to AI applications in hospital management. This MOOC is a quick start to the applications of AI for this class of professionals, focusing entirely on deep learning, particularly on smart and AI-based automation in the healthcare sector. It aims to propagate ideas about how to proactively engage with AI in the healthcare domain.
The course will help participants bridge the gap between healthcare and technology. Participants will possess the knowledge and confidence to engage with AI projects, advocate for responsible AI adoption, and identify opportunities to leverage AI for better patient outcomes and operational efficiency.
This course will provide you with a solid understanding of AI’s capabilities, benefits, and limitations, as well as actionable strategies to contribute to AI-driven innovation in your organization. You will learn how to:
Identify common tasks that can be solved with AI models.
Develop and train AI models to automate certain tasks in a medical environment
Visualize the inner workings of the models trained in this program ("understandable AI").
Mitigate challenges related to the clinical use of AI, such as AI mistrust, and legal and ethical considerations
Discuss AI in medical settings.
Module 1 : Overview of AI in Clinical Environments
Module 2 : Automatic Diagnosis of Respiratory Disease With AI
Module 3 : Automatic Segmentation Analysis of Medical Images
Module 4 : Automatic Enhancements of Medical Images
Module 5 : AI in Histology
Module 6 : AI Mistrust and Explainable AI
Module 7 : Mental Health and AI
Module 8: The Challenges of AI in Healthcare
Module 9 : The Future of AI in Healthcare
Associate Professor, College of Science and Engineering • Hamad Bin Khalifa University
Associate Professor, College of Science and Engineering • Hamad Bin Khalifa University
Professor, College of Science and Engineering • Hamad Bin Khalifa University