Journal of neuroengineering and rehabilitation
Dec 19, 2025
BACKGROUND: Stroke is a condition marked by considerable variability in lesions, recovery trajectories, and responses to therapy. Consequently, precision medicine in rehabilitation post-stroke, which aims to deliver the "right intervention, at the ri...
Atrial fibrillation (AF) significantly contributes to the incidence of strokes. Screening for AF enhances its detection and effective management. However, universal AF screening in rural areas poses a challenge. This study evaluates the cost-effectiv...
The erratic nature of cardiac rhythms can precipitate a multitude of pathologies. Consequently, the endeavor to achieve stabilization of the human heartbeat has garnered significant scholarly interest in recent years. In this context, an adaptive non...
Regime switching in a time series is an important and challenging issue in complex financial system analysis. Existing regime models have focused on the features of fluctuations at a single point in financial time series, often neglecting time series...
BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide and poses a heavy burden on health care systems. Early screening for CRC through colonoscopy can effectively reduce both the incidence and mortality associated with CRC. Ho...
Alterations in brain connectivity provide early indications of neurodegenerative diseases like Alzheimer's disease (AD). Here, we present a novel framework that integrates a Hidden Markov Model (HMM) within the architecture of a convolutional neural ...
In this paper, we study the impact of momentum, volume and investor sentiment on U.S. tech sector stock returns using Principal Component Analysis-Hidden Markov Model (PCA-HMM) methodology. Price and volume are two well-known aspects in general equil...
BACKGROUND: The Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the c...
As crowdsourcing emerges as an efficient and cost-effective method for obtaining labels for machine learning datasets, it is important to assess the quality of crowd-provided data to improve analysis performance and reduce biases in subsequent machin...
This work proposes a new hybrid model for joint indoor localization and activity recognition by combining a Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU) model with a Markov Random Field (MRF) for better classification. The CNN-GRU succ...
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