• Dr.M.Vasumathi Devi
• Dr.G.Rajesh Chandra
• Angirekula Swetha
• Nadendla Abhinaya Sri
• Gujju Prasanna Lakshmi , Shaik Najma

The evolution of medical product monitoring systems has been significantly transformed by the advent of automated technologies. This paper delves into the advancements, regulatory aspects, challenges, and future directions of automated monitoring systems for medical products. Automated monitoring systems, leveraging technologies such as the Artificial Intelligence (AI), offer unprecedented precision and efficiency in tracking the safety and efficacy of medical products. These systems play a crucial role in ensuring compliance with stringent regulatory frameworks set forth by global bodies like the FDA and EMA, as well as local regulations. The introduction of automated systems in medical product monitoring addresses several critical issues faced by traditional methods, including human error, delayed reporting, and data inaccuracies. By automating the monitoring processes, these systems can provide real- time data collection, analysis, and reporting, thereby enhancing the overall reliability of the monitoring process. The integration of AI algorithms allows for advanced data analytics, predictive modeling, and anomaly detection, further contributing to proactive safety measures and timely intervention

Healthcare, Automated Monitoring, Patient, Medical Products, Regulatory aspects, Leveraging technology, Anomaly detection, Data Analytics, Reporting, Data collection, Prediction modeling, Analysis, Human error

"AUTOMATED MONITORING IN HEALTHCARE: LEVERAGING AI FOR IMPROVED PATIENT OUTCOMES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.378-387, October-2024, Available :http://www.jetir.org/papers/JETIRGN06042.pdf

"AUTOMATED MONITORING IN HEALTHCARE: LEVERAGING AI FOR IMPROVED PATIENT OUTCOMES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp378-387, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06042.pdf