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AI comes to the Nobel Prize and drug discovery.
J Pharm Anal
November 2024
College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou 310058, China.
The association between total social exposure and incident multimorbidity: A population-based cohort study.
SSM Popul Health
March 2025
Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, Ontario, M5T 3M7, Canada.
Background: Multimorbidity, the co-occurrence of two or more chronic conditions, is associated with the social determinants of health. Using comprehensive linked population-representative data, we sought to understand the combined effect of multiple social determinants on multimorbidity incidence in Ontario, Canada.
Methods: Ontario respondents aged 20-55 in 2001-2011 cycles of the Canadian Community Health Survey were linked to administrative health data ascertain multimorbidity status until 2022.
Multimodal artificial intelligence system for detecting a small esophageal high-grade squamous intraepithelial neoplasia: A case report.
World J Gastrointest Endosc
January 2025
Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Background: Recent advancements in artificial intelligence (AI) have significantly enhanced the capabilities of endoscopic-assisted diagnosis for gastrointestinal diseases. AI has shown great promise in clinical practice, particularly for diagnostic support, offering real-time insights into complex conditions such as esophageal squamous cell carcinoma.
Case Summary: In this study, we introduce a multimodal AI system that successfully identified and delineated a small and flat carcinoma during esophagogastroduodenoscopy, highlighting its potential for early detection of malignancies.
Advancing precision cancer immunotherapy drug development, administration, and response prediction with AI-enabled Raman spectroscopy.
Front Immunol
January 2025
Department of Surgery, Stanford School of Medicine, Stanford University Medical Center, Stanford, CA, United States.
Molecular characterization of tumors is essential to identify predictive biomarkers that inform treatment decisions and improve precision immunotherapy development and administration. However, challenges such as the heterogeneity of tumors and patient responses, limited efficacy of current biomarkers, and the predominant reliance on single-omics data, have hindered advances in accurately predicting treatment outcomes. Standard therapy generally applies a "one size fits all" approach, which not only provides ineffective or limited responses, but also an increased risk of off-target toxicities and acceleration of resistance mechanisms or adverse effects.
View Article and Find Full Text PDFDetecting anomalies in smart wearables for hypertension: a deep learning mechanism.
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
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