Machine Learning in Modern Healthcare: From Genomics to Clinical Decision Support

Abstract

The integration of Artificial Intelligence and Machine Learning technologies is fundamentally transforming healthcare delivery, particularly in medical diagnosis, treatment planning, and drug discovery. This article explores how deep learning models, specifically Convolutional Neural Networks and Recurrent Neural Networks, are revolutionizing medical imaging analysis and predictive health monitoring. The implementation of these technologies enables healthcare organizations to leverage real-time data processing and scalable solutions through cloud platforms and big data tools. It provides the application of predictive models in early disease detection, particularly for conditions such as cancer, Alzheimer's, and heart diseases, demonstrating superior accuracy compared to traditional methods. It also addresses the challenges of AI implementation in healthcare, including data privacy concerns, annotated dataset requirements, and regulatory compliance, while highlighting the significant advancements in personalized medicine through genetic analysis and tailored treatment approaches.

Ähnliche Arbeiten