Introduction to Artificial Intelligence for Radiographers

Program Overview

This short course from City, University of London introduces radiographers to the basics of Artificial Intelligence (AI) and its applications in radiography. Participants will gain essential knowledge of AI concepts, explore its potential impact on the field, and prepare for a future where AI plays a significant role in healthcare. The course emphasizes practical application, ethical considerations, and career opportunities in AI for radiographers.

Program Outline

Degree Overview:

Introduction to Artificial Intelligence for Radiographers

is a short course offered by City, University of London, designed to introduce radiographers to the basics of Artificial Intelligence (AI) and its applications in the field of radiography.

Key Objectives:

• Equip radiographers with essential knowledge and understanding of AI concepts and principles.
• Explore the potential impact of AI on radiography practice.
• Analyze the challenges and opportunities presented by AI in the field.
• Prepare radiographers for a future with AI in healthcare.

Program Description:

This course is delivered over one week, and includes a combination of on-campus lectures, online discussions, and self-directed learning. The curriculum covers a wide range of topics, including:

• Background and Rationale of AI in Medical Imaging
• Strengths, Weaknesses, Opportunities, and Threats of AI in Radiography
• Applications of AI in Different Radiography Contexts
• AI Ethics and Accountability
• Patient Acceptability of AI
• Impact of AI on Clinical Practice, Workflow, and Patient Pathway

Outline:

Course Structure:

• The course is divided into four days of on-campus lectures and one day of online activities.
• Each day covers specific topics related to AI in radiography.
• Participants are expected to engage in discussions, complete assignments, and participate in self-directed learning activities.

Modules:

• Module 1: Introduction to AI
• Definition of AI
• History and evolution of AI
• Different types of AI
• Applications of AI in various fields
• Module 2: AI in Medical Imaging
• Role of AI in healthcare
• Applications of AI in medical imaging
• Benefits and challenges of AI in medical imaging
• Module 3: AI in Radiography
• Specific applications of AI in radiography
• Impact of AI on radiography practice
• Challenges and opportunities presented by AI in radiography
• Module 4: AI Ethics and Patient Acceptability
• Ethical considerations of AI in healthcare
• Patient privacy and data security
• Public perception of AI in healthcare
• Module 5: Future of AI in Radiography
• Potential future applications of AI in radiography
• Implications of AI for the future of radiography profession
• Preparing for a future with AI in radiography

Assessment:

Formative Assessment:

• Participants will receive feedback on a 300-word abstract of written work on an AI topic of their choice.
• The feedback will focus on the student's understanding of the topic, critical thinking, and ability to synthesize information.

Summative Assessment (Optional):

• Participants can choose to take assessments to earn credits towards a postgraduate program.
• The assessments will consist of a written abstract on a case study and an oral presentation.
• The presentations will be evaluated based on the student's ability to effectively communicate their understanding of the topic, analyze data, and draw conclusions.

Teaching:

Teaching Methods:

• The course utilizes a variety of teaching methods, including:
• Interactive lectures
• Group discussions
• Case studies
• Hands-on activities
• Self-directed learning

Faculty:

• The course is taught by experts in the field of AI and radiography.
• The faculty includes:
• Researchers
• Clinicians
• Industry professionals

Unique Approach:

• The course emphasizes practical application of AI in radiography.
• Participants have the opportunity to learn from experts in the field and discuss real-world scenarios.
• The course also addresses the ethical and social implications of AI in healthcare.

Careers:

Potential Career Paths:

• The course can help prepare radiographers for a variety of career paths, including:
• AI specialist in radiography
• Research scientist in AI and medical imaging
• Clinical lead in AI implementation
• Educator in AI for healthcare professionals

Career Opportunities:

• The course can open doors to new career opportunities in the growing field of AI in healthcare.
• Graduates can work in hospitals, research institutions, and technology companies.

Career Outcomes:

• Graduates of the course will be well-equipped to:
• Understand the potential impact of AI on radiography practice.
• Adapt to the changing landscape of healthcare with the integration of AI.
• Contribute to the development and implementation of AI solutions in radiography.
• Advocate for the ethical and responsible use of AI in healthcare.

Other:

• The course is designed to be flexible and can be taken as a standalone CPD course or as part of a postgraduate program in MRI/CT.
• Participants who successfully complete the assessments can earn 30 credits towards a postgraduate program.
• The course is open to radiographers, researchers, and other healthcare professionals who are interested in learning more about AI in radiography.