Prashant shares fascinating insights about the challenges of training machine learning models with radiological images. He highlights how different settings of radiology machines can lead to variations in data quality, impacting model performance. An intriguing story unfolds as he recounts their initial success with a small dataset of chest x-rays mined from the internet, which surprisingly yielded high accuracy in distinguishing normal from abnormal images.
