A machine learning integrated SERS sensing platform is developed for a single-shot, receptor-free, rapid detection and classification of five respiratory viruses including Influenza A, Respiratory Syncytial Virus (RSV), Human Rhinoviruses (Rhino), an...
Staphylococcus aureus (S. aureus) is the leading risk factor for food safety and human health. Herein, a novel wavelength-selective machine learning -driven adaptive strand exchange amplification (SEA)/SERS biosensor was developed for rapid detection...
By utilizing the synergistic effects of a dual-metal cobalt@copper electrode and advanced machine learning algorithms, we have developed a reliable and cost-effective electrochemical sensor for creatinine monitoring. The sensor's active surface was f...
Cysteamine (CA) serves as a cystine-depleting agent employed in the management of cystinosis and a range of other medical conditions. Monitoring blood CA levels at the point of care is imperative due to the risk of toxicity associated with elevated C...
Electrochemiluminescence (ECL)-based point-of-care testing (POCT) has the potential to facilitate the rapid identification of diseases, offering advantages such as high sensitivity, strong selectivity, and minimal background interference. However, as...
Carbapenem resistance and hypervirulence represent two distinct evolutionary pathways in , posing significant challenges in clinical settings. Of particular concern are convergent strains that combine both traits, complicating timely diagnosis and tr...
Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
Jan 1, 2025
Surface-enhanced Raman scattering (SERS) is a transformative technique for molecular identification, offering exceptional sensitivity, signal specificity, and resistance to photobleaching, making it invaluable for disease diagnosis, monitoring, and s...
Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
Jul 25, 2023
Transmission electron microscopy (TEM) imaging can be used for detection/localization of gold nanoparticles (GNPs) within tumor cells. However, quantitative analysis of GNP-containing cellular TEM images typically relies on conventional/thresholding-...
We report the development of deep-learning coherent electron diffractive imaging at subangstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained ...
The ability to identify virus particles is important for research and clinical applications. Because of the optical diffraction limit, conventional optical microscopes are generally not suitable for virus particle detection, and higher resolution ins...
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