Develop NLP Models for Medical Data Extraction

Description

Radiology reports follow a standard format with key sections that medical specialists must complete when analyzing patient scans. This Build Project focuses on developing a machine learning model that can automatically segment radiology reports into these standard sections, such as title, indication, technique, comparisons, findings, and impression. You'll take on the role of a Machine Learning Engineer, applying natural language processing techniques to build predictive models that extract these sections from unstructured text. You'll learn to represent text as embeddings, visualize data, and implement MLOps to automate training, evaluation and deployment of these machine learning models. These skills—ranging from NLP to MLOps—are in high demand across industries, equipping you with practical experience relevant to entry-level roles in AI-driven healthcare, data science, and machine learning engineering. As automation and AI continue to reshape the workforce, expertise in building, deploying, and optimizing machine learning models is essential for addressing real-world challenges in healthcare and beyond.