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@article{171603,
        author = {MOHSIN AH MIR and Nahida bilal and Towqeer bashir and Aaqib bhat},
        title = {Revolutionizing Radiology: AI-Powered Disease Detection and Diagnosis in  Healthcare},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {8},
        pages = {347-351},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171603},
        abstract = {Radiology is an essential diagnostic tool, traditional radiography has limitations when it comes to accuracy, efficiency, and individualized care. Different approaches are required due to the increasing amount of medical images and the possibility of human mistake. The application of artificial intelligence (AI) to radiography promises revolutionary improvements in disease detection and diagnosis in terms of accessibility, efficiency, and accuracy. This study examines the state of AI-driven radiology now and its prospects for the future, with a particular emphasis on deep learning methods, machine learning algorithms, and advanced image analytics. Artificial intelligence (AI) systems can greatly increase the early detection rates of a variety of diseases, such as cancer, cardiovascular ailments, and neurological problems, by analysing massive datasets and identifying patterns beyond the capabilities of human beings. AI-powered solutions also enable quicker diagnosis, which lessens the workload for radiologists and allows for more timely and individualised treatment options. The difficulties and moral issues surrounding the use of AI in clinical settings are also covered in this paper. These issues include algorithmic bias, data privacy, and the requirement for strong validation procedures.},
        keywords = {Artificial Intelligence, Radiology, Precision Healthcare, Disease Diagnosis, and Medical Imaging, natural language processing (NLP) , electronic health records (EHRs) .},
        month = {December},
        }