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Development of a Cohort Analytics Tool for Monitoring Progression Patterns in Cardiovascular Diseases: Advanced Stochastic Modeling Approach.
JMIR Med Inform
September 2024
Department of Information Systems and Business Analytics, College of Business, Loyola Marymount University, Los Angeles, CA, United States.
Background: The World Health Organization (WHO) reported that cardiovascular diseases (CVDs) are the leading cause of death worldwide. CVDs are chronic, with complex progression patterns involving episodes of comorbidities and multimorbidities. When dealing with chronic diseases, physicians often adopt a "watchful waiting" strategy, and actions are postponed until information is available.
View Article and Find Full Text PDFA Parametric Model for Characterizing Time-Variant Single Trials of Block-Design fNIRS Experiments.
Annu Int Conf IEEE Eng Med Biol Soc
July 2023
Block-design is a popular experimental paradigm for functional near-infrared spectroscopy (fNIRS). Traditional block-design analysis techniques such as generalized linear modeling (GLM) and waveform averaging (WA) assume that the brain is a time-invariant system. This is a flawed assumption.
View Article and Find Full Text PDFJoint frequency space design approach for efficient planar frequency diverse arrays.
Sci Rep
July 2023
Engineering, Computer Science and Visual Arts Integrated Complex, Concordia University, Montreal, H3G 1M8, Canada.
Antenna arrays offer advantages in terms of spatial diversity, allowing for control over pattern specifications in space. The incorporation of frequency diversity in arrays presents an opportunity to manipulate beams in the Space-Time domain. Unlike conventional arrays, Frequency Diverse Arrays (FDA) with added frequency diversity exhibit time-variant and range-dependent patterns.
View Article and Find Full Text PDFReliability-Based Large-Vocabulary Audio-Visual Speech Recognition.
Sensors (Basel)
July 2022
Institute of Communication Acoustics, Ruhr University Bochum, 44801 Bochum, Germany.
Audio-visual speech recognition (AVSR) can significantly improve performance over audio-only recognition for small or medium vocabularies. However, current AVSR, whether hybrid or end-to-end (E2E), still does not appear to make optimal use of this secondary information stream as the performance is still clearly diminished in noisy conditions for large-vocabulary systems. We, therefore, propose a new fusion architecture-the decision fusion net (DFN).
View Article and Find Full Text PDFLocalizing Spectral Interactions in the Resting State Network Using the Hilbert-Huang Transform.
Brain Sci
January 2022
Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei 11031, Taiwan.
Article Synopsis
- The study explores how brain synchronizations are influenced by neuronal oscillations and their frequency interactions, particularly focusing on resting-state fMRI (rs-fMRI) to better understand these dynamics.
- Instead of using traditional Fourier-based methods, the researchers utilized the Hilbert-Huang transform (HHT) to achieve a higher resolution in analyzing frequency interactions within brain regions, revealing important insights about functional integration.
- The findings highlight that the amplitude-to-amplitude frequency couplings differ between eye-closed and eye-open states, suggesting that the ESI technique can enhance our understanding of brain connectivity and may have implications for clinical neuroscience.
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