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At least 217 records · Page 12Linked to original sources
PubMed2001

The use of artificial intelligence in the design of an intelligent cognitive orthosis for people with dementia.

Dementia often reduces a person's ability to perform activities of daily living because he or she becomes confused and cannot remember the sequence of steps to perform. The current solution is to have a caregiver continually supervise and assist the person using verbal reminders or cues. This loss of privacy and increased dependency may cause the affected person to become embarrassed and agitated. We propose that this situation might be improved by using a computerized device that monitors progress and provides the reminders needed. The COACH is a first prototype of such a device. It uses artificial intelligence to observe a user, learn from his or her actions, and issue prerecorded cues of varying detail. The device was developed using a personal computer and a video camera that unobtrusively tracked the user. Preliminary testing with subjects who simulated confused behavior as they washed their hands showed that the device was performing its functions with an efficacy of approximately 95%. More extensive clinical testing and evaluation has begun, and the results will be reported in future publications.

Activities of Daily Living↗
PubMed2026

Privacy-Preserving Linkage of Distributed Biological, Clinical, and Imaging Data Supporting Artificial Intelligence in Pediatric Oncology.

BACKGROUND: Cancer remains the leading cause of disease-related mortality in children over the age of one in Europe, with over 35,000 new pediatric cases and more than 6,000 deaths annually. Due to the rarity of pediatric cancers, clinical trial protocols often substitute for formal treatment guidelines, resulting in many children being enrolled in multiple trials, with biological samples and genomic data stored in various biobanks. Data collection in pediatric oncology is challenging, with sparse data acquired over extended periods, underscoring the need for optimal utilization of all available information through linked, privacy-preserving datasets. METHODS: Here, we report the development of a distributed, privacy-preserving data infrastructure for the PRIMAGE project, a European initiative aimed at supporting artificial intelligence (AI)-driven image analysis for pediatric cancer prognostics. The infrastructure leverages the European Patient Identity (EUPID) Services for Privacy-Preserving Record Linkage, enabling pseudonymized data integration across clinical, biological, and imaging sources. The system incorporates EUPID's hashing and phonetic matching protocols to pseudonymize patient identifiers and link distributed datasets, facilitating secondary data use in compliance with the General Data Protection Regulation. RESULTS: Data from over 700 neuroblastoma patients from European trials and hospitals were linked and uploaded to the PRIMAGE platform, where AI models predict clinical outcomes. CONCLUSION: This infrastructure successfully facilitated AI model development, advancing pediatric oncology research, and offering a scalable framework for future European health data initiatives, such as the European Health Data Space.

Journal Article↗
PubMed1998

Smart X-ray beam position monitor system using artificial-intelligence methods for the Advanced Photon Source insertion-device beamlines.

At the Advanced Photon Source (APS), each insertion-device (ID) beamline front end has two X-ray beam position monitors (XBPMs) to monitor the X-ray beam position for both vertical and horizontal directions. Performance challenges for a conventional photoemission-type XBPM during operations are contamination of the signal from the neighbouring bending-magnet sources and the sensitivity of the XBPM to the insertion-device gap variations. Problems are exacerbated because users change the ID gap during their operations, and hence the percentage level of the contamination in the front-end XBPM signals varies. A smart XBPM system with a high-speed digital signal processor has been built at the Advanced Photon Source for the ID beamline front ends. The new version of the software, which uses an artificial-intelligence method, provides a self-learning and self-calibration capability to the smart XBPM system. The structure of and recent test results with the system are presented in this paper.

Journal Article↗
PubMed1990

Structural alerts to genotoxicity: the interaction of human and artificial intelligence.

The assignments of 'structural alerts' by Ashby and associates as predictors of genotoxic carcinogenicity were used as the entries for CASE, an artificial intelligence-based structure-activity relational method. CASE, using this human intelligence-based information, was able to derive structural determinants that duplicate the informational content of the structural alerts (sensitivity, 0.974; specificity, 0.948). The CASE-predicted alerts performed as well as the results of the Salmonella mutagenicity assay or the direct application of structural alerts in predicting carcinogens.

Artificial Intelligence↗