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@article{200805,
        author = {Savitri Pandurang Birajdar},
        title = {Artificial intelligence in healthcare :Improving Diagnostic Accuracy through deep learning and using several approaches},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1695-1697},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200805},
        abstract = {AI is transforming current healthcare by significantly improving diagnostic accuracy and minimizing treatment strategies. AI also improving clinical decision making [2],[3].This paper presents review of AI driven techniques, particularly deep learning models such as convolutional neural networks(CNN),Recurrent Neural Networks (RNNs), and transformer-based architectures, in medical diagnostics [6], [7].As compared to human ,AI systems perform better in applications like radiology, pathology , dermatology and ophthalmology.[4],[5].
The study also shows several approaches in AI systems integrating image processing, electronic health records for deep diagnosis. Apart from notable advancements, there are many challenges such as data bias, lack of interpretability and privacy concerns[2]. This paper majorly analyzes these limitations and proposes future directions including explainable AI and personalized medicine[10],[15].The findings highlight AI as a powerful enabler of precision healthcare.},
        keywords = {},
        month = {May},
        }