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Artificial Intelligence in Medical Diagnosis: From Medical Imaging to Predictive Analytics
Abstract
Artificial intelligence (AI) has revolutionized medical diagnosis by offering innovative tools and algorithms that enhance accuracy, efficiency, and patient outcomes across various healthcare domains. This paper explores the applications of AI in medical diagnosis, focusing on its integration into medical imaging interpretation and predictive analytics. Key topics include machine learning algorithms, deep learning architectures, and natural language processing techniques used to analyze medical images, such as X-rays, MRIs, and histopathological slides, for the detection and characterization of diseases. Additionally, the paper discusses the role of AI in predictive analytics, risk stratification, and decision support systems, enabling personalized treatment recommendations and preventive interventions. Furthermore, the paper examines the regulatory considerations, ethical implications, and challenges associated with the implementation of AI-based diagnostic tools in clinical practice. By synthesizing evidence from research studies and clinical trials, this paper aims to illustrate the transformative potential of AI in revolutionizing medical diagnosis and improving patient care delivery.
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References
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