Successful visualization of the odor discrimination process in an AI-assisted olfactory sensor
Peer-Reviewed Publication
Updates every hour. Last Updated: 3-Apr-2026 19:15 ET (3-Apr-2026 23:15 GMT/UTC)
NIMS has been developing chemical sensors as a key component of the artificial olfaction technology (olfactory sensors), with the aim of putting this technology into practical use. In this study, explainable AI (XAI) was used to reveal how chemical sensors discriminate among various odorant molecules. The findings may help guide the selection of receptor materials for developing high-performance chemical sensors capable of detecting odorant molecules. The achievement is expected not only to improve the performance of artificial olfaction but also to advance understanding of human olfactory mechanisms. This research was published online in ACS Applied Materials & Interfaces on September 9, 2025.
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In a real-world clinical trial, published in JAMA Network Open, researchers demonstrate that a fully digital AI zero-cost method for detecting dementia can be scaled across primary care clinics. This breakthrough represents a major step forward in translating AI and patient-reported outcomes into everyday clinical care. By integrating scalable digital tools that operate seamlessly within existing health systems, the research team demonstrated how technology can strengthen early detection and improve outcomes for older adults as well as reduce burdens on primary care teams. The AI tool, which has been in development for more than 10 years at Regenstrief Institute, is a machine learning algorithm that uses natural language processing to analyze data from electronic health records. It identifies information such as memory issues, vascular concerns and other factors linked to dementia.