Understanding Data in Medical Artificial Intelligence for Healthcare Professionals

Data is essential for any AI system. This module aims to clarify the following topics:

 

Types of Healthcare Data:

Learn about structured and unstructured data, including clinical notes, imaging, vital signs, laboratory results, and more.

 

Data Science Pipeline:

Explore the process from data collection and cleaning to feature engineering and creating training/testing splits.

 

Model Training and Evaluation:

Gain insights into key concepts such as accuracy, precision, recall, F1 score, and the importance of validation.

 

Real-World Challenges:

Understand issues like bias, data privacy, interoperability, and maintaining data quality over time.

 

Why It Matters:

AI is only as effective as the data it learns from. As clinicians, it's our responsibility to comprehend how data is utilised in AI to ensure clinical validity and patient safety.

 

CPD Awarded: 7 CPD, with approximately 7 hours required to complete the module plus exam time.