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http://dx.doi.org/10.3389/fnins.2023.1275481 | DOI Listing |
Polymers (Basel)
December 2024
School of Mechanical Engineering, Yeungnam University, 280, Daehak-ro, Gyeongsan 38541, Republic of Korea.
Polymer composites have gained attention due to their multifunctionality and ability to tune properties at multiple scales [...
View Article and Find Full Text PDFPersistence barcodes emerge as a promising tool in radiological analysis, offering a novel approach to reduce bias and uncover hidden patterns in medical imaging. By leveraging topological data analysis, this technique provides a robust, multi-scale perspective on image features, potentially overcoming limitations in traditional methods and Graph Neural Networks. While challenges in interpretation and implementation remain, persistence barcodes show significant potential for improving diagnostic accuracy, standardization, and ultimately, patient outcomes in the evolving field of radiology.
View Article and Find Full Text PDFJ Physiol
September 2024
Department of Physiology and Biophysics, Dalhousie University, Halifax, Canada.
Comput Biol Med
October 2024
School of Software, Jiangxi Normal University, Nanchang, China. Electronic address:
Deep learning plays a pivotal role in retinal blood vessel segmentation for medical diagnosis. Despite their significant efficacy, these techniques face two major challenges. Firstly, they often neglect the severe class imbalance in fundus images, where thin vessels in the foreground are proportionally minimal.
View Article and Find Full Text PDFBioinform Adv
June 2024
Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Cluster of Excellence 'Controlling Microbes to Fight Infections', Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard Karl University of Tübingen, Tübingen 72076, Germany.
Motivation: In recent years, applying computational modeling to systems biology has caused a substantial surge in both discovery and practical applications and a significant shift in our understanding of the complexity inherent in biological systems.
Results: In this perspective article, we briefly overview computational modeling in biology, highlighting recent advancements such as multi-scale modeling due to the omics revolution, single-cell technology, and integration of artificial intelligence and machine learning approaches. We also discuss the primary challenges faced: integration, standardization, model complexity, scalability, and interdisciplinary collaboration.
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