HJBR Nov/Dec 2024

50 NOV / DEC 2024 I  HEALTHCARE JOURNAL OF BATON ROUGE MEDICAID COLUMN MEDICAID ARTIFICIAL INTELLIGENCE (AI) has rapidly transformed healthcare by enabling new methodologies for data analysis and predictive modeling. Machine learning (ML) and deep learning (DL), as primary drivers of AI, provide powerful tools for analyzing vast and complex medical data, assisting in clinical decision-making, and optimizing healthcare processes. While ML algorithms rely on structured data and often require domain-specif- ic feature engineering, DL models, particularly neural networks, excel at extracting intri- cate patterns from unstructured data such as medical images, text, and genomic sequenc- es. 1 Choosing between these techniques depends on the nature of the problem, the quality and quantity of data, and the desired outcomes. Here, we will dive into the theoretical foundations, applications, and challenges of ML and DL in healthcare. MACHINE LEARNING vs. DEEP LEARNING IN HEALTHCARE