AIMC Topic: Reproducibility of Results

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A deep learning-based multisite neuroimage harmonization framework established with a traveling-subject dataset.

NeuroImage
The accumulation of multisite large-sample MRI datasets collected during large brain research projects in the last decade has provided critical resources for understanding the neurobiological mechanisms underlying cognitive functions and brain disord...

A Deep-Learning-Based Health Indicator Constructor Using Kullback-Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures.

Sensors (Basel, Switzerland)
This paper proposes a new technique for the construction of a concrete-beam health indicator based on the Kullback-Leibler divergence (KLD) and deep learning. Health indicator (HI) construction is a vital part of remaining useful lifetime (RUL) appro...

A deep learning based method for intelligent detection of seafarers' mental health condition.

Scientific reports
Mental health monitoring of seafarers is an important part of achieving normal development of the ocean shipping industry. In this paper, a dual subjective-objective testing scheme is proposed to achieve a more effective and intelligent assessment of...

Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment.

Computational intelligence and neuroscience
Accurate emotion analysis of teaching evaluation texts can help teachers effectively improve the quality of education and teaching. In order to improve the precision and accuracy of emotion analysis, this paper proposes an emotion recognition and ana...

SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.

Journal of biomedical semantics
BACKGROUND: The high volume of research focusing on extracting patient information from electronic health records (EHRs) has led to an increase in the demand for annotated corpora, which are a precious resource for both the development and evaluation...

Feature Optimization Method of Material Identification for Loose Particles Inside Sealed Relays.

Sensors (Basel, Switzerland)
Existing material identification for loose particles inside sealed relays focuses on the selection and optimization of classification algorithms, which ignores the features in the material dataset. In this paper, we propose a feature optimization met...

Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.

Scientific reports
An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset....

Reconfigurable Artificial Synapses with Excitatory and Inhibitory Response Enabled by an Ambipolar Oxide Thin-Film Transistor.

ACS applied materials & interfaces
A gate-tunable synaptic device controlling dynamically reconfigurable excitatory and inhibitory synaptic responses, which can emulate the fundamental synaptic responses for developing diverse functionalities of the biological nervous system, was deve...

Analysis of Deep Learning-Based Phase Retrieval Algorithm Performance for Quantitative Phase Imaging Microscopy.

Sensors (Basel, Switzerland)
Quantitative phase imaging has been of interest to the science and engineering community and has been applied in multiple research fields and applications. Recently, the data-driven approach of artificial intelligence has been utilized in several opt...

Evaluation of Smart City Sustainable Development Prospects Based on Fuzzy Comprehensive Evaluation Method.

Computational intelligence and neuroscience
In this study, the method of a fuzzy comprehensive evaluation is used to analyze the research situation of smart city development, and 20 evaluation indicator systems are selected as the original indicator database; the relevant sustainable developme...