Category: 7. Maths

Biomedical telemetry is an emerging interdisciplinary domain where body vitals are transmitted wirelessly for detailed observation and analysis¹. Significant advancements in semiconductor technology have led to numerous breakthroughs, providing…

Clinical free text preprocessing and institutional pairwise analyses

The final dataset consisted of 1,607,393 procedures: 44 institutions covering 48 distinct anesthesiology CPT codes (From 3,566,343 procedures, 432,039 were removed due to missing…

In this study, we implemented a two-stage deep learning-based framework for the classification and segmentation of chest diseases using Chest X-ray (CXR) images, focusing specifically on five categories: The study examines five distinct…

This study develops and designs an LBCCD-GJO method for IoT. The proposed method’s major intention is to identify and classify cybersecurity in the blockchain-assisted IoT environment. To accomplish this, the proposed LBCCD-GJO model involves…

Tai Chi movement assessment neural network model design

Our neural network model for Tai Chi movement assessment builds upon the Spatial-Temporal Graph Convolutional Network (ST-GCN) architecture, enhanced with attention mechanisms to capture the…

Data sources and preprocessing

The data used in this study is sourced from publicly available information channels such as the Guotai’an database, Giant Tide Information Network, and company annual reports, covering quarterly financial and…

Overview of the SleepNet model

The SleepNet model presents an innovative method for detecting sleep apnea by utilizing various physiological signals to improve diagnostic precision. At the heart of its design is a hybrid framework that merges a…

We used the pre-trained xECGArch¹⁵ to classify 1521 unseen ECGs into AF and n-AF. Subsequently model explanations were extracted in terms of each sample’s relevance for classification using DTD for both, the long-term and the short-term…

In the following section, we outline a proposed architecture for the rail track sensory system, aligning with the framework outlined in²⁶ and²⁷. Figure 2 depicts the simplified representation of the proposed model. We strategically deploy sensors…

Figure 1 demonstrates the ConvMHANet model architecture for HaiNan dialect to Mandarin. First, a corpus for model training is created by collecting and labeling dialectal speech data from different regions of HaiNan (e.g., WenChang, WanNing,…