AIMC Topic: Humans

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A novel approach for joint indoor localization and activity recognition using a hybrid CNN-GRU and MRF framework.

PloS one
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...

Instantaneous center of rotation, the first step to build up the digital laboratory of complex motions.

PloS one
Calculating instantaneous centers of rotation to describe combined rotational and translational motions has a long history in many fields of applied science and basic rigid body kinematics. However, only some theoretical studies have explored the fun...

Robust skeletal motion tracking using temporal and spatial synchronization of two video streams.

PloS one
Accurate and reliable skeletal motion tracking is essential for rehabilitation monitoring, enabling objective assessment of patient progress and facilitating telerehabilitation applications. Traditional marker-based motion capture systems, while high...

GNN-RMNet: Leveraging graph neural networks and GPS analytics for driver behavior and route optimization in logistics.

PloS one
Logistics networks are becoming increasingly complex and rely more heavily on real-time vehicle data, necessitating intelligent systems to monitor driver behavior and identify route anomalies. Traditional techniques struggle to capture the dynamic sp...

Advancing smart communities with a deep learning framework for sustainable resource management.

PloS one
BACKGROUND: The rapid development of urban systems and rising requirements for sustainable development lift resource management issues in smart communities. A fundamental problem for contemporary communities involves effectively using energy and wate...

AI-Assisted identification of sex-specific patterns in diabetic retinopathy using retinal fundus images.

PloS one
Diabetic retinopathy (DR) is a microvascular complication of diabetes that can lead to blindness if left untreated. Regular monitoring is crucial for detecting early signs of referable DR, and the progression to moderate to severe non-proliferative D...

Reducing bias in coronary heart disease prediction using Smote-ENN and PCA.

PloS one
Coronary heart disease (CHD) is a major cardiovascular disorder that poses significant threats to global health and is increasingly affecting younger populations. Its treatment and prevention face challenges such as high costs, prolonged recovery per...

Distribution of interscan measurement error in AI-based 3D MRI analysis of knee cartilage thickness in osteoarthritis.

PloS one
PURPOSE: A novel AI-based 3D analysis system was developed to automatically extract bone and cartilage from MRI data and provide average cartilage thickness. This study aimed to analyze the interscan measurement error of knee cartilage thickness in o...

TRI-PLAN: A deep learning-based automated assessment framework for right heart assessment in transcatheter tricuspid valve replacement planning.

International journal of cardiology
BACKGROUND: Efficient and accurate preoperative assessment of the right-sided heart structural complex (RSHSc) is crucial for planning transcatheter tricuspid valve replacement (TTVR). However, current manual methods remain time-consuming and inconsi...

Pred5AOP: an efficient screening of food-derived antioxidant peptides based on deep learning, molecular docking, and experimental validation.

Food chemistry
Antioxidant peptides derived from dietary proteins positively impact human health due to their high activity and safety. In this study, a database of 76,343 peptides was constructed via in silico hydrolysis of 29 dietary proteins. A novel antioxidant...