AIMC Topic: Neural Networks, Computer

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Energy-efficient communication between IoMT devices and emergency vehicles for improved patient care.

PloS one
The rising integration of emergency healthcare services with the Internet of Medical Things (IoMT) creates a significant opportunity to improve real-time communication between patients and emergency vehicles like ambulances. Fast and reliable data in...

Deep Unfolded Variable Projection Networks.

International journal of neural systems
In this paper, we present a hybrid learning framework that integrates two model-driven AI paradigms: Deep unfolding and Variable Projections (VPs). The core idea is to unfold the iterations of VP solvers for separable nonlinear least squares (SNLLS) ...

Basic Stability Tests of Machine Learning Potentials for Molecular Simulations in Computational Drug Discovery.

Journal of chemical information and modeling
Neural network potentials trained on quantum-mechanical data can calculate molecular interactions with relatively high speed and accuracy. However, not all neural network potentials are suitable for molecular simulations, as they might exhibit instab...

A heart failure classification model from radial artery pulse wave using LSTM neural networks.

BMC medical informatics and decision making
BACKGROUND: Heart failure (HF) represents a pressing global health issue demanding innovative and accessible approaches for early detection. Non-invasive, rapid, and cost-effective techniques utilizing deep learning (DL) hold significant promise for ...

Cox proportional hazards model with Bayesian neural network for survival prediction.

Scientific reports
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...

Chinese crop diseases and pests named entity recognition based on variational information bottleneck and feature enhancement.

Scientific reports
Chinese crop diseases and pests named entity recognition (CCDP-NER) is a critical step in extracting domain-specific information in the field of crop diseases and pests, playing a significant role in promoting agricultural informatization. To address...

Stock market forecasting research based on GA-WOA-LSTM.

PloS one
With the increasing complexity and prosperity of global financial markets, stock market forecasting plays a critical role in investment decision-making, market regulation, and economic planning. This study proposes a hybrid prediction model that inte...

Enhancing Toxicity Prediction of Synthetic Chemicals via Novel SMILES Fragmentation and Interpretable Deep Learning.

Journal of chemical information and modeling
Toxicity prediction and identification of structural alerts (SAs) for synthetic chemicals are critical for assessing risks to environmental and human health. Traditional methods, which rely heavily on molecular descriptors, often suffer from poor int...

A comparative analysis of deep learning architectures for thyroid tissue classification with hyperspectral imaging.

Scientific reports
Hyperspectral imaging has shown significant applicability in the medical field, particularly for its ability to represent spectral information that can differentiate specific biomolecular characteristics in tissue samples. However, the complexity of ...

Improved pulmonary embolism detection in CT pulmonary angiogram scans with hybrid vision transformers and deep learning techniques.

Scientific reports
Pulmonary embolism (PE) represents a severe, life-threatening cardiovascular condition and is notably the third leading cause of cardiovascular mortality, after myocardial infarction and stroke. This pathology occurs when blood clots obstruct the pul...