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Artificial Intelligence Based Automated Medical Imaging Analysis and Interpretation

Sangeeta Jawar, Ramgopal Kashyap

202536 citationsDOI

Abstract

Adding artificial intelligence (AI) to medical imaging has changed how diagnoses are made by making it possible to look at images, especially chest X-rays, more accurately and automatically. This study investigates how advanced AI techniques, such as deep learning and neural networks, can automate the assessment of the cardiothoracic ratio, a crucial indicator for identifying heart diseases. AI uses huge records and complicated formulas to make medical findings better, faster, and more consistent, so humans don't have to look them over as often. The study also examines the challenges that arise from combining AI, such as inaccurate data and errors, and emphasizes the importance of conducting comprehensive reviews to evaluate the effectiveness of these AI-powered solutions. This study shows how AI could greatly improve patient results by helping to find and diagnose cardiovascular diseases earlier using computerized medical image analysis.

Topics & Concepts

Computer scienceInterpretation (philosophy)Artificial intelligenceMedical imagingNatural language processingProgramming languageRadiomics and Machine Learning in Medical ImagingMachine Learning in HealthcareArtificial Intelligence in Healthcare and Education
Artificial Intelligence Based Automated Medical Imaging Analysis and Interpretation | Litcius