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@article{178152,
        author = {Aishwarya T S and Kumbha Gayathri Ram and Dr. T N Anitha},
        title = {Stethoscope Guided by Artificial Intelligence: A  Smart Healthcare Approach},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2411-2412},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178152},
        abstract = {With the advent of artificial intelligence (AI) and Internet of Things (IoT), the traditional stethoscope has been transformed into a smart diagnostic tool. This paper presents a system wherein heart and lung sounds are recorded through an electronic stethoscope, processed using signal filtering techniques, and then analyzed by a machine learning model trained to classify cardiac anomalies. The system allows real-time auscultation, anomaly detection, and remote health monitoring, thereby enhancing accessibility and early diagnosis, particularly in rural and underserved areas. The frontend interface is developed using HTML, CSS, and JavaScript, while the backend leverages Python with Django and machine learning libraries. This fusion of AI, IoT, and healthcare represents a step towards smarter, scalable, and more accurate diagnostic systems.},
        keywords = {AI Stethoscope, Heart Sound Classification, Machine Learning, Biomedical Signal Processing, IoT in Healthcare, Digital Auscultation, Telemedicine},
        month = {May},
        }