Abstract
Background: Radiology diagnosis has been dramatically changed with the help of progressive technologies in imaging. AI integration in healthcare has improved forecasts hence improving the diagnostic capabilities of the systems.
Aim: This research seeks to delve on effectiveness of AI in radiology interpretation as compared to human interpretation. It defines the concept of Artificial Intelligence and its relation to diagnostic procedures, reliability and relevance.
Methods: Comparative analysis design was adopted for the study and comparative methods included AI algorithms and human radiologists. The imaging data in the form of X-ray, CT or MRI were collected and the diagnostic reports were brought to a common format for the study. These comparative parameters included sensitivity, specificity, as well as overall accuracy, with the help of statistical techniques. Results: This research revealed that the effectiveness of AI is equivalent or perhaps even more efficient in terms of diagnostic accuracy to human radiology. Real- life examples brought out the strengths of AI especially on interpretation and the tremendous time it takes to do so.
Conclusion: AI has potential in improving the quality and speed of diagnosis in radiology setting. However, the following areas are critical to achieving the integration of AMR into routine clinical practice: Technological improvements and ethical issues.
Keywords: Radiology Diagnostics, Artificial Intelligence, Comparative Analysis, Diagnostic Accuracy, Healthcare Technology.