AIMC Topic: Neural Networks, Computer

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Fully automated workflow for designing patient-specific orthopaedic implants: Application to total knee arthroplasty.

PloS one
Background Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to treat joint osteoarthritis, reducing pain and improving mobility. Nevertheless, a significant share ...

Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.

PloS one
Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic plans. Despite its importance, achieving precise forecasts remains a formidable challenge. To tackle...

A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks.

PloS one
This paper presents a novel framework for detecting and predicting abnormal traffic events on highways. Current traffic monitoring systems often rely on single data sources, which limits their detection accuracy and robustness in complex environments...

PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation.

PloS one
Human pose estimation (HPE) has made significant progress with deep learning; however, it still faces challenges in handling occlusions, complex poses, and complex multi-person scenarios. To address these issues, we propose PoseNet++, a novel approac...

Application of IRSA-BP neural network in diagnosing diabetes.

PloS one
Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. This study focuses on this key area of diabetes prediction and aims to develop an innova...

A lightweight spiking neural network for EEG-based motor imagery classification.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs) aim to simulate the human brain neural network, using sparse spike event streams for effective and energy-efficient spatio-temporal signal processing. This paper proposes a lightweight SNN model for electroencephalogram...

CTFS: A consolidated transformer framework for instance and semantic segmentation tasks.

Neural networks : the official journal of the International Neural Network Society
Instance segmentation and semantic segmentation are fundamental tasks that support many computer vision applications. Recently, researchers have investigated the feasibility of constructing a unified transformer framework and leveraging multi-task le...

GraphCF: Drug-target interaction prediction via multi-feature fusion with contrastive graph neural network.

Artificial intelligence in medicine
Drug-target interaction (DTI) is paramount in drug discovery and repurposing, which involves screening for effective candidate drugs by targeting specific proteins. Existing methods often focus on one or two representations of drugs or targets, and l...

Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients.

Experimental gerontology
BACKGROUND: Type 2 diabetes (T2D) has been established as an independent risk factor for osteoporosis, often resulting in a poor prognosis. Thus, it is crucial for clinicians to diagnose osteoporosis in diabetic patients. This study aimed to develop ...

Artificial intelligence for predicting the risk of bone fragility fractures in osteoporosis.

European radiology experimental
Osteoporosis is widespread with a high incidence rate, resulting in fragility fractures which are a major contributor to mortality among the elderly. Artificial intelligence (AI), in particular artificial neural networks, appears to be useful in mana...