Revolutionizing Patient Diagnosis with Machine Learning Precision

Abstract

Artificial intelligence is reforming healthcare systems by enabling faster and more accurate diagnoses. However, its true potential remains largely untapped due to challenges in data integration, supervision, and interpretability. This research explores how machine learning models, particularly deep learning algorithms, enhance diagnosis accuracy by analyzing patient medical data in real time. AI frameworks incorporating convolutional neural networks (CNNs) for image-based diagnostics and natural language processing for clinical notes interpretation can significantly reduce misdiagnosis rates and personalize treatment plans.