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Digital Solutions for the Optimization of Pharmacologic Therapy for Heart Failure.
JACC Heart Fail
January 2025
Cardiovascular Division, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Data from large-scale, randomized, controlled trials demonstrate that contemporary treatments for heart failure (HF) can substantially improve morbidity and mortality. Despite this, observed outcomes for patients living with HF are poor, and they have not improved over time. The are many potential reasons for this important problem, but inadequate use of optimal medical therapy for patients with HF, an important component of guideline-directed medical therapy, in routine practice is a principal and modifiable contributor.
View Article and Find Full Text PDFDesigning a Multivariate Belt Conveyor Idler Stall Detection and Identification System with Scalability Analysis.
Sensors (Basel)
December 2024
Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Pohang 37673, Republic of Korea.
Belt conveyor idlers are freely rotating idlers supporting the belt of a conveyor, and can induce severe frictional damage to the belt as they fail. Therefore, fast and accurate detection of idler faults is crucial for the effective maintenance of belt conveyor systems. In this article, we implement and evaluate the performance of an idler stall detection system based on a multivariate deep learning model using accelerometers and microphone sensor data.
View Article and Find Full Text PDFDeepGOMeta for functional insights into microbial communities using deep learning-based protein function prediction.
Sci Rep
December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
View Article and Find Full Text PDFUniFORM: Towards Universal Immunofluorescence Normalization for Multiplex Tissue Imaging.
bioRxiv
December 2024
Department of Biomedical Engineering and Computational Biology Program, OHSU, Portland, OR, USA.
Multiplexed tissue imaging (MTI) technologies enable high-dimensional spatial analysis of tumor microenvironments but face challenges with technical variability in staining intensities. Existing normalization methods, including z-score, ComBat, and MxNorm, often fail to account for the heterogeneous, right-skewed expression patterns of MTI data, compromising signal alignment and downstream analyses. We present UniFORM, a non-parametric, Python-based pipeline for normalizing both feature- and pixel-level MTI data.
View Article and Find Full Text PDFCHIP-ing Away at Post-Transplant Outcomes: the Role of Somatic Mutations in Heart Transplant Outcomes.
J Card Fail
December 2024
Division of Cardiology, Duke University School of Medicine, Durham, North Carolina; Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina; Duke Center for Precision Health, Duke University School of Medicine, Durham, North Carolina. Electronic address:
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