Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly pre...
We present an automated method to track and identify neurons in , called 'fast Deep Neural Correspondence' or fDNC, based on the transformer network architecture. The model is trained once on empirically derived semi-synthetic data and then predicts ...
This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer...
Computational intelligence and neuroscience
Jul 14, 2021
In high-paced and efficient life and work, fatigue is one of the important factors that cause accidents such as traffic and medical accidents. This study designs a feature map-based pruning strategy (PFM), which effectively reduces redundant paramete...
Supplier selection is an important decision-making problem, which involves many quantitative and qualitative factors incorporating vagueness and imprecision. This study proposes a novel fuzzy multi-criteria decision-making framework for supplier sele...
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients fr...
Neural networks : the official journal of the International Neural Network Society
Jul 13, 2021
Depth estimation from a single image frame is a fundamental challenge in computer vision, with many applications such as augmented reality, action recognition, image understanding, and autonomous driving. Large and diverse training sets are required ...
Computer methods and programs in biomedicine
Jul 13, 2021
Background and Objective Electrocardiogram (ECG) quality assessment is significant for automatic diagnosis of cardiovascular disease and reducing the massive workload of reviewing continuous ECGs. Hence, how to design an appropriate algorithm for obj...
Spatial co-location detection is the task of inferring the co-location of two or more objects in the geographic space. Mobile devices, especially a smartphone, are commonly employed to accomplish this task with the human object. Previous work focused...
To better understand the behavior of attackers and describe the network state, we construct an LSTM-DT model for network security situation awareness, which provides risk assessment indicators and quantitative methods. This paper introduces the conce...
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