As almonds are prone to oxidation during storage, it is essential to construct a real-time method to monitor the quality of almonds efficiently. In this study, the in situ detection was developed using whole-cell biosensor combined with machine learn...
Diabetes is a growing global health concern, affecting millions and leading to severe complications if not properly managed. The primary challenge in diabetes management is maintaining blood glucose levels (BGLs) within a safe range to prevent compli...
Frontiers in cellular and infection microbiology
Apr 16, 2025
OBJECTIVES: Urinary tract infection is one of the most prevalent forms of bacterial infection, and prompt and efficient identification of pathogenic bacteria plays a pivotal role in the management of urinary tract infections. In this study, we propos...
Advanced materials (Deerfield Beach, Fla.)
Apr 10, 2025
Medical micro- and nano-bots (MMBs and MNBs) have attracted a lot of attention owing to their precise motion for accessing difficult-to-reach areas in the body. These emerging tools offer the promise of non-invasive diagnostics and therapeutics for a...
The integration of Artificial Intelligence (AI) techniques with medical kits has revolutionized disease diagnosis, enabling rapid and accurate identification of various conditions. We developed a novel deep learning model, namely DeepATsers based on ...
Fibrous bioelectronic provides an intrinsically accessible platform for artificial nerve and real-time physiological perception. However, advanced fiber-based artificial synapse remains a challenge due to the contradictory conductance demands for bra...
Accurate molecular biomarker detection with digital-resolution sensitivity is essential for applications such as disease diagnostics, therapeutic studies, and biomedical research. Here, we present LOCA-PRAM (LOcalization with Context Awareness), a de...
Point-of-care testing (POCT) with multiplexed capability, ultrahigh sensitivity, affordable smart devices, and user-friendly operation is critically needed for clinical diagnostics and food safety. This study presents a deep-learning-assisted microfl...
Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to ex...
A deep learning algorithm is introduced to accurately predict glucose concentrations using colorimetric paper sensor (CPS) images. We used an image dataset from CPS treated with five different glucose concentrations as input for deep learning models....
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