Pyrethroid pesticide residues pose a significant global public health challenge, particularly in complex edible fungus matrices where trace, structurally similar pesticides are difficult to distinguish and detect. To address this critical gap, a nove...
Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the potential of AgNPs as DM2 treatment agent using in vitro, in vivo, and machine learning approaches. M...
Transient ischemic attack (TIA) serves as a critical early warning sign for ischemic stroke. Its timely identification holds significant clinical value in reducing recurrence risk and improving patient prognosis. However, existing detection methods e...
Pathogenic bacteria pose serious threats to public health and environmental safety. Conventional colony counting, a standard method for bacterial detection, is time-consuming and unsuitable for rapid on-site detection. In this work, a flexible ACH/Ag...
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...
The detection of soluble arsenic in realgar and its preparations is crucial for toxicity evaluation. Therefore, surface-enhanced Raman spectroscopy (SERS) combined with machine learning was applied for the rapid detection of soluble As3+ in realgar a...
Inspired by the perception and temperature regulation functionalities of human skin, multifunctional electronic skin (E-skin) for human motion detection and personal thermal management has attracted great attention. Here, we design an E-skin with str...
The evolution of biosensors demands synergistic improvements in signal transduction and data processing. We present a universal biosensing platform that combines dual-mode signal responses from silver-modulated gold nanorods (AuNRs) and gold-silver n...
In this study, we introduce a machine learning optimized graphene-based biosensor tailored for the early and accurate detection of breast cancer, aiming to elevate diagnostic reliability and clinical efficacy. The device employs a multilayer Ag-SiO₂-...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.