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Alzheimers Dement
December 2024
Penn Neurodegeneration Genomics Center, Dept of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Article Synopsis
- NIAGADS is a national data repository providing access to genomic data related to Alzheimer's disease, focusing on curating and standardizing information from various sources for researchers.
- To improve data navigation, NIAGADS has developed AI enhancements using large language models trained on its documentation and API, which help users with complex queries and facilitate data discovery.
- These AI improvements include rule-based chatbots and generative search tools that respond to user inquiries, learn from feedback, and assist in common issues, ultimately enhancing the overall user experience on NIAGADS platforms.
Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dynamic digital representations of patients, offer opportunities for personalized headache management by integrating diverse datasets such as neuroimaging, multiomics, and wearable sensor data to advance headache research, optimize treatment, and enable virtual trials. In addition, AI-driven wearable devices equipped with next-generation biosensors combined with multi-agent chatbots could enable real-time physiological and biochemical monitoring, diagnosing, facilitating early headache attack forecasting and prevention, disease tracking, and personalized interventions.
View Article and Find Full Text PDFMultiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer.
Insights Imaging
January 2025
Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in management and prognosis. MRI may play an important diagnostic role in this setting.
View Article and Find Full Text PDFRecent advances in SERS assays for detection of multiple extracellular vesicles biomarkers for cancer diagnosis.
Nanoscale
January 2025
School of Natural Sciences, Faculty of science and engineering, Macquarie University, Sydney, NSW 2109, Australia.
Article Synopsis
- The rising incidence of cancer has created a pressing need for improved early detection tools, highlighting the importance of identifying specific biomarkers for accurate diagnosis.
- Cancer-derived small extracellular vesicles (sEVs) have emerged as a promising biomarker, given their abundance in body fluids and their rich assortment of biological indicators.
- Surface-enhanced Raman scattering (SERS) technology is gaining traction for its ability to quickly and sensitively detect cancer sEVs using various innovative assays, paving the way for enhanced early detection and classification of cancers in clinical settings.
Deception detection in educational AI: challenges for Japanese middle school students in interacting with generative AI robots.
Front Artif Intell
December 2024
School of Systems Information Science, Future University Hakodate, Hakodate, Hokkaido, Japan.
Educational materials that utilize generative AI (e.g., ChatGPT) have been developed, thus, allowing students to learn through conversations with robots or agents.
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