Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.emc.2015.09.001 | DOI Listing |
Appl Sci (Basel)
June 2024
Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE 68182, USA.
Understanding metabolic cost through biomechanical data, including ground reaction forces (GRFs) and joint moments, is vital for health, sports, and rehabilitation. The long stabilization time (2-5 min) of indirect calorimetry poses challenges in prolonged tests. This study investigated using artificial neural networks (ANNs) to predict metabolic costs from the GRF and joint moment time series.
View Article and Find Full Text PDFGastroenterol Hepatol
January 2025
Pharmacoeconomics & Outcomes Research Iberia (PORIB), Madrid, España. Electronic address:
Introduction: A significant percentage of patients coinfected with hepatitis B virus (HBV) and hepatitis D virus (HDV) are undiagnosed. Coinfected patients progress to advanced liver disease faster than HBV monoinfected patients, thereby consuming more healthcare resources. The aim was to perform an analysis to determine the cost of hidden HDV infection in Spain.
View Article and Find Full Text PDFJ Cogn Neurosci
December 2024
In natural and artificial neural networks, modularity and distributed structure afford complementary but competing benefits. The former allows for hierarchical representations that can flexibly recombine modules to address novel problems, whereas the latter can benefit from less constrained training, potentially uncovering fruitful statistical regularities. Here, we investigate these competing demands in the context of human sequential behavior.
View Article and Find Full Text PDFJ Drug Target
January 2025
Department of Pharmaceutics, Bharat Pharmaceutical Technology, Amtali, Agartala, Tripura, India.
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.
View Article and Find Full Text PDFSci Rep
December 2024
College of Information Engineering, Yancheng Teachers University, Yancheng, 224002, China.
Incremental broad learning system (IBLS) is an effective and efficient incremental learning method based on broad learning paradigm. Owing to its streamlined network architecture and flexible dynamic update scheme, IBLS can achieve rapid incremental reconstruction on the basis of the previous model without the entire retraining from scratch, which enables it adept at handling streaming data. However, two prominent deficiencies still persist in IBLS and constrain its further promotion in large-scale data stream scenarios.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!