The paper "Artificial Intelligence-Powered Electrochemical Sensor: Recent Advances, Challenges, and Prospects" by Siti Nur Ashakirin Binti Mohd Nashruddin, Faridah Hani Mohamed Salleh, Rozan Mohamad Yunus, and Halimah Badioze Zaman, published in the Institute of Informatics and Computing in Energy (ICEE) and Fuel Cell Institute, discusses the integration of artificial intelligence (AI) with electrochemical biosensors. This integration is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective when combined with AI, which adeptly identifies, categorizes, characterizes, and projects intricate data patterns. The paper highlights critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, such as data privacy, sensor stability, and algorithmic bias, the integration of AI into biosensor systems shows immense promise for creating future medical devices that can provide early detection and improved patient outcomes. Key advancements include the use of AI algorithms to enhance the sensitivity and selectivity of electrochemical biosensors, enabling real-time monitoring and prediction capabilities. Wearable biosensors, integrated with smartphones, offer portable and continuous monitoring of physiological parameters and biomarkers, enhancing personalized healthcare and telemedicine systems. Challenges such as data interpretation, integration, power consumption, user acceptance, regulatory compliance, and cost-effectiveness are also discussed. The paper concludes by emphasizing the transformative potential of AI in advancing medical diagnostics and personalized treatment, while also highlighting the need for further research to address existing challenges and capitalize on opportunities in the field.The paper "Artificial Intelligence-Powered Electrochemical Sensor: Recent Advances, Challenges, and Prospects" by Siti Nur Ashakirin Binti Mohd Nashruddin, Faridah Hani Mohamed Salleh, Rozan Mohamad Yunus, and Halimah Badioze Zaman, published in the Institute of Informatics and Computing in Energy (ICEE) and Fuel Cell Institute, discusses the integration of artificial intelligence (AI) with electrochemical biosensors. This integration is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective when combined with AI, which adeptly identifies, categorizes, characterizes, and projects intricate data patterns. The paper highlights critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, such as data privacy, sensor stability, and algorithmic bias, the integration of AI into biosensor systems shows immense promise for creating future medical devices that can provide early detection and improved patient outcomes. Key advancements include the use of AI algorithms to enhance the sensitivity and selectivity of electrochemical biosensors, enabling real-time monitoring and prediction capabilities. Wearable biosensors, integrated with smartphones, offer portable and continuous monitoring of physiological parameters and biomarkers, enhancing personalized healthcare and telemedicine systems. Challenges such as data interpretation, integration, power consumption, user acceptance, regulatory compliance, and cost-effectiveness are also discussed. The paper concludes by emphasizing the transformative potential of AI in advancing medical diagnostics and personalized treatment, while also highlighting the need for further research to address existing challenges and capitalize on opportunities in the field.