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Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.
Stat Methods Med Res
January 2025
School of Mathematics, Sun Yat-sen University, Guangzhou, Guangdong, China.
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most existing individualized treatment rule estimation methods were developed for the studies with binary treatments.
View Article and Find Full Text PDFA 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Safety of tenecteplase vs. alteplase in telestroke: a large multistate experience (STAT).
Front Neurol
January 2025
TeleSpecialists, LLC, Fort Myers, FL, United States.
Introduction: Prompt treatment with IV thrombolytics (IVT) in acute ischemic stroke (AIS) patients is critical for improved recovery and survival. Recently, hospital systems have switched to the IVT tenecteplase (TNK) instead of the FDA-approved alteplase (tPA) for treatment. Multiple studies and meta-analyses evaluating the efficacy and safety of TNK demonstrate similar or superior outcomes when compared to tPA.
View Article and Find Full Text PDFSafety of combined drug use in patients with cardiovascular and cerebrovascular diseases: an analysis based on the spontaneous reporting database of adverse drug reactions in Hubei Province.
Front Pharmacol
January 2025
School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Objective: There is a lack of studies investigating the safety of combination regimens specifically for cardiovascular and cerebrovascular diseases. This study aimed to evaluate the safety of combination drugs for cardiovascular and cerebrovascular diseases using real-world data.
Methods: We analyzed adverse drug reaction data received by the Hubei Adverse Drug Reaction Center from the first quarter of 2014 to the fourth quarter of 2022.
Introduction: Tuberculosis (TB) poses a significant threat to global health, with millions of new infections and approximately one million deaths annually. Various modeling efforts have emerged, offering tailored data-driven and physiologically-based solutions for novel and historical compounds. However, this diverse modeling panorama may lack consistency, limiting result comparability.
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