AIMC Topic: Humans

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Analysis of collapse risks under cut and cover method based on multi-state fuzzy Bayesian network.

PloS one
The collapse accidents under cut and cover method in metro station construction occurred frequently, leading to severe casualties and property damage. With increasing of metro station construction in China, more and more attention has been paid to co...

A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one
BACKGROUND: Predicting protein-DNA binding sites in vivo is a challenging but urgent task in many fields such as drug design and development. Most promoters contain many transcription factor (TF) binding sites, yet only a few have been identified thr...

Forecasting second-hand house prices in China using the GA-PSO-BP neural network model.

PloS one
While the traditional genetic algorithms are capable of forecasting house prices, they often suffer from premature convergence, which adversely affects the reliability of the forecasts. To address this issue, the research employs a genetic-particle s...

CLAAF: Multimodal fake information detection based on contrastive learning and adaptive Agg-modality fusion.

PloS one
The widespread disinformation on social media platforms has created significant challenges in verifying the authenticity of content, especially in multimodal contexts. However, simple modality fusion can introduce much noise due to the differences in...

Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dynamic brain networks are more effective than static networks in characterizing the evolving patterns of brain functional connectivity, making them a more promising tool for diagnosing neurodegenerative diseases. However, existing classification met...

Efficient, Robust, and Accurate CNN Predictor for Neuronal Activation in Directional Deep Brain Stimulation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The programming of clinical deep brain stimulation (DBS) systems involves numerous combinations of stimulation parameters, such as stimulus amplitude, pulse width, and frequency. As more complex electrode designs, such as directional electrodes, are ...

FDC: Feature Dropout Consistency for unsupervised domain adaptation semantic segmentation.

Neural networks : the official journal of the International Neural Network Society
In Unsupervised Domain Adaptation Semantic Segmentation (UDASS), while self-training techniques have become one of the most effective methods to date, the absence of target labels makes models susceptible to overfitting. To address this problem, cons...

Knowledge-guided adaptive spatial-temporal graph contrastive learning framework: Regional crop diseases prediction based on electronic medical records.

Neural networks : the official journal of the International Neural Network Society
The occurrence of crop diseases exhibits nonlinear and dynamic spatial-temporal correlations. How to realize real-time and accurate regional disease prediction is an emerging challenge in smart agriculture. Existing research is hindered by difficulti...

Semi-supervised segmentation on medical images with pseudo label calibration and neural process.

Neural networks : the official journal of the International Neural Network Society
Pseudo supervision has demonstrated empirical success in semi-supervised segmentation tasks by effectively leveraging unlabeled data, but it unavoidably encounters the problem caused by noisy pseudo labels. Existing methods against noisy pseudo label...

Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.

Ear and hearing
OBJECTIVES: Despite the extensive use of machine learning (ML) models in health sciences for outcome prediction and condition classification, their application in differentiating various types of auditory disorders remains limited. This study aimed t...