Experiential richness creates tissue-level changes and synaptic plasticity as patterns emerge from rhythmic spatiotemporal activity of large interconnected neuronal assemblies. Despite numerous experimental and computational approaches at different s...
Artificial intelligence (AI) has received great attention since the concept was proposed, and it has developed rapidly in recent years with applications in many fields. Meanwhile, newer iterations of smartphone hardware technologies which have excell...
Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples...
Classification and sorting of cells using image-activated cell sorting (IACS) systems can bring significant insight to biomedical sciences. Incorporating deep learning algorithms into IACS enables cell classification and isolation based on complex an...
A novel, portable, and smartphone-based molecularly imprinted polymer electrochemiluminescence (MIP-ECL) sensing platform was constructed for sensitive and selective determination of furosemide (FSM). In this platform, MoSe nanoparticles/starch-deriv...
Soft robotics have substantial benefits of safety, adaptability, and cost efficiency compared to conventional rigid robotics. Textiles have applications in soft robotics either as an auxiliary material to reinforce the conventional soft material or a...
Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short ...
Artificial intelligence (AI) and wearable sensors are two essential fields to realize the goal of tailoring the best precision medicine treatment for individual patients. Integration of these two fields enables better acquisition of patient data and ...
In this work, we explore the performance of plasmonic biosensor designs that integrate metamaterials based on machine learning algorithms. The meta-plasmonic biosensors were designed for optimized detection of DNA with a layer of double negative meta...