AIMC Topic: Neural Networks, Computer

Clear Filters Showing 1921 to 1930 of 31376 articles

Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks.

BMC cancer
OBJECTIVE: The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment ...

DeepATsers: a deep learning framework for one-pot SERS biosensor to detect SARS-CoV-2 virus.

Scientific reports
The integration of Artificial Intelligence (AI) techniques with medical kits has revolutionized disease diagnosis, enabling rapid and accurate identification of various conditions. We developed a novel deep learning model, namely DeepATsers based on ...

Optimized driver fatigue detection method using multimodal neural networks.

Scientific reports
Driver fatigue is a significant factor contributing to road accidents, highlighting the need for precise and reliable detection systems. This study introduces a comprehensive approach using multimodal neural networks, leveraging the DROZY dataset, wh...

MLG2Net: Molecular Global Graph Network for Drug Response Prediction in Lung Cancer Cell Lines.

Journal of medical systems
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines be...

CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.

Scientific reports
Sleep posture, a vital aspect of sleep wellness, has become a crucial focus in sleep medicine. Studies show that supine posture can lead to a higher occurrence of obstructive sleep apnea, while lateral posture might reduce it. For bedridden patients,...

Classification of schizophrenia based on RAnet-ET: resnet based attention network for eye-tracking.

Journal of neural engineering
There is a notable need of quantifiable and objective methods for the classification of schizophrenia. Patients with schizophrenia exhibit atypical eye movements compared with healthy individuals. To address this need, we have developed a classificat...

Quantitative detection of serum biochemical indexes via UV-Vis-NIRS combined with deep neural networks.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
To achieve rapid, cost-efficient, convenient and accurate detection of five clinical serum biochemical indexes, namely glucose (GLU), triglycerides (TG), total cholesterol (TC), total protein (TP) and albumin (ALB), ultraviolet-visible-near infrared ...

Intermediate data fusion improves the accuracy of near-infrared spectroscopy and Raman spectroscopy for the detection of aflatoxin B1 in peanuts.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study developed a convolutional neural network (CNN) model based on feature-level data fusion for quantitatively detecting aflatoxin B1 (AFB1) in peanuts. Using a portable near-infrared (NIR) spectrometer and a Raman spectrometer, NIR and Raman ...

TCH: A novel multi-view dimensionality reduction method based on triple contrastive heads.

Neural networks : the official journal of the International Neural Network Society
Multi-view dimensionality reduction (MvDR) is a potent approach for addressing the high-dimensional challenges in multi-view data. Recently, contrastive learning (CL) has gained considerable attention due to its superior performance. However, most CL...

Safe and accelerated screening framework for support tensor machines.

Neural networks : the official journal of the International Neural Network Society
Support Tensor Machines (STMs) constitute an effective supervised learning method for classifying high-dimensional tensor data. However, traditional iterative solving methods are often time-consuming. To effectively address the issue of lengthy train...