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This study examined the application of GPT-4 with vision (GPT-4V), a multimodal large language model with visual recognition, in detecting radiologic findings from a set of 100 chest radiographs and suggests that GPT-4V is currently not ready for real-world diagnostic usage in interpreting chest radiographs. 

Wearable sweat biosensors offer compelling opportunities for improved personal health monitoring and non-invasive measurements of key biomarkers. Inexpensive device fabrication methods are necessary for scalable manufacturing of portable, disposable, and flexible sweat sensors. Furthermore, real-time sweat assessment must be analyzed to validate measurement reliability at various sweating rates. Here, we demonstrate a “smart bandage” microfluidic platform for cortisol detection and continuous glucose monitoring integrated with a synthetic skin. The low-cost, laser-cut microfluidic device is composed of an adhesive-based microchannel and solution-processed electrochemical sensors fabricated from inkjet-printed graphene and silver solutions. An antibody-derived cortisol sensor achieved a limit of detection of 10 pM and included a low-voltage electrowetting valve, validating the microfluidic sensor design under typical physiological conditions. To understand effects of perspiration rate on sensor performance, a synthetic skin was developed using soft lithography to mimic human sweat pores and sweating rates. The enzymatic glucose sensor exhibited a range of 0.2 to 1.0 mM, a limit of detection of 10 μM, and reproducible response curves at flow rates of 2.0 μL min −1 and higher when integrated with the synthetic skin, validating its relevance for human health monitoring. These results demonstrate the potential of using printed microfluidic sweat sensors as a low-cost, real-time, multi-diagnostic device for human health monitoring.