AI-Assisted Nanosensors and Intelligent Signal Analysis for Precision Biosensing in Healthcare

Biosensors and biomolecular electronics are becoming increasingly important in healthcare, where rapid, sensitive, and reliable detection is needed for diagnosis, monitoring, and personalized intervention. In particular, nanosensors offer major advantages through high surface area, enhanced sensitivity, low sample requirements, and potential for miniaturized and point-of-care use. At the same time, modern biosensing platforms generate complex signals that can be difficult to interpret using conventional analytical approaches alone. Artificial intelligence, machine learning, and advanced signal-processing methods are therefore emerging as valuable tools for improving biosensor accuracy, selectivity, robustness, and clinical usability. This Research Topic will highlight advances at the intersection of nanosensor development, intelligent signal analysis, and healthcare-oriented biosensing, with a focus on practical diagnostic and monitoring applications.The goal of this Research Topic is to gather innovative contributions on the design, optimization, and application of nanoscale biosensors and biomolecular electronic systems enhanced by artificial intelligence and intelligent data analysis. We welcome studies that integrate sensor engineering with machine learning, pattern recognition, or biosignal-processing approaches to improve analytical sensitivity, specificity, reproducibility, and real-time decision support. Particular interest will be given to work involving biomarker detection, electrochemical or nanomaterial-based biosensing, intelligent interpretation of sensor outputs, and data-driven strategies for early disease detection and health monitoring. We also encourage submissions on portable, wearable, implantable, or point-of-care biosensing devices in which AI-supported analysis strengthens device performance or translational value. By linking nanosensor innovation with computationally informed interpretation, this Research Topic aims to advance smart biosensing systems that are more accurate, scalable, and clinically useful.This Research Topic welcomes original research, reviews, mini reviews, methods, and perspective articles. Topics of interest include nanosensors, biosensor fabrication, biomolecular electronics, electrochemical and nanomaterial-based biosensors, intelligent sensor readout, AI-assisted biosignal analysis, biomarker detection, point-of-care diagnostics, wearable or implantable biosensors, and healthcare monitoring platforms. Submissions using artificial intelligence or machine learning are encouraged when they are directly linked to biosensor development, optimization, validation, or diagnostic interpretation. Manuscripts should demonstrate clear relevance to healthcare applications and to biosensors or biomolecular electronics. Studies focused mainly on general AI methods, physical sensors, medical imaging, or non-biomedical engineering applications are outside the intended scope of this collection. Topic editors: Ibrahim Isik, Xiangling Li, Eden Morales-Narváez Source: https://www.frontiersin.org/research-topics/80707/ai-assisted-nanosensors-and-intelligent-signal-analysis-for-precision-biosensing-in-healthcare