AIMC Topic: Algorithms

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PFENet: Towards precise feature extraction from sparse point cloud for 3D object detection.

Neural networks : the official journal of the International Neural Network Society
Accurate 3D point cloud object detection is crucially important for autonomous driving vehicles. The sparsity of point clouds in 3D scenes, especially for smaller targets like pedestrians and bicycles that contain fewer points, makes detection partic...

MDWConv:CNN based on multi-scale atrous pyramid and depthwise separable convolution for long time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Long time series forecasting has extensive applications in various fields such as power dispatching, traffic control, and weather forecasting. Recently, models based on the Transformer architecture have dominated the field of time series forecasting....

DKiS: Decay weight invertible image steganography with private key.

Neural networks : the official journal of the International Neural Network Society
Image steganography, defined as the practice of concealing information within another image. In this paper, we propose decay weight invertible image steganography with private key (DKiS). This model introduces two major advancements into current inve...

Illuminating the unseen: Advancing MRI domain generalization through causality.

Medical image analysis
Deep learning methods have shown promise in accelerated MRI reconstruction but face significant challenges under domain shifts between training and testing datasets, such as changes in image contrasts, anatomical regions, and acquisition strategies. ...

Identifying multilayer network hub by graph representation learning.

Medical image analysis
The recent advances in neuroimaging technology allow us to understand how the human brain is wired in vivo and how functional activity is synchronized across multiple regions. Growing evidence shows that the complexity of the functional connectivity ...

Automatic machine learning accurately predicts the efficacy of immunotherapy for patients with inoperable advanced non-small cell lung cancer using a computed tomography-based radiomics model.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individual...

The use of Artificial Intelligence Algorithms in drug development and clinical trials: A scoping review.

International journal of medical informatics
BACKGROUND: Artificial Intelligence (AI) is transforming drug development and clinical trials, helping researchers find new treatments faster and personalize care for patients. By automating tasks like molecule screening and predicting treatment outc...

Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.

International journal of molecular sciences
The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate between severe and mild cases. Furthermore, the use of artificial intelligence (AI) and machine learning ...

Investigating the key principles in two-step heterogeneous transfer learning for early laryngeal cancer identification.

Scientific reports
Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosis. Some disease classification tasks can rely on large homogeneous public datasets to train the transferred model, while others cannot, i.e., endoscop...

Mitochondrial segmentation and function prediction in live-cell images with deep learning.

Nature communications
Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image seg...