AIMC Topic: Neural Networks, Computer

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Effective Phoneme Decoding With Hyperbolic Neural Networks for High-Performance Speech BCIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
OBJECTIVE: Speech brain-computer interfaces (speech BCIs), which convert brain signals into spoken words or sentences, have demonstrated great potential for high-performance BCI communication. Phonemes are the basic pronunciation units. For monosylla...

Lightweight Neural Network for Sleep Posture Classification Using Pressure Sensing Mat at Various Sensor Densities.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recently, pressure-sensing mats have been widely used to capture static and dynamic pressure over sleep for posture recognition. Both a full-size mat with a low-density sensing array for figuring out the structure of the whole body and a miniature sc...

Bio-inspired deep neural local acuity and focus learning for visual image recognition.

Neural networks : the official journal of the International Neural Network Society
In the field of computer vision and image recognition, enabling the computer to discern target features while filtering out irrelevant ones poses a challenge. Drawing insights from studies in biological vision, we find that there is a local visual ac...

SSR-DTA: Substructure-aware multi-layer graph neural networks for drug-target binding affinity prediction.

Artificial intelligence in medicine
Accurate prediction of drug-target binding affinity (DTA) is essential in the field of drug discovery. Recently, scientists have been attempting to utilize artificial intelligence prediction to screen out a significant number of ineffective compounds...

[Development and validation of a tool for the systematic identification of social vulnerabilities in cancer patients: the DEFCO tool].

Bulletin du cancer
INTRODUCTION: Literature suggests that patients from deprived backgrounds are less likely to adhere to their treatments, continue to expose themselves to risk factors and, as a result, have poorer health outcomes. It is therefore crucial to identify ...

Using neural networks for image analysis in general physiology.

The Journal of general physiology
An article with three goals, namely, to (1) provide the set of ideas and information needed to understand, at a basic level, the application of convolutional neural networks (CNNs) to analyze images in biology; (2) trace a path to adopting and adapti...

Development of message passing-based graph convolutional networks for classifying cancer pathology reports.

BMC medical informatics and decision making
BACKGROUND: Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language...

Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis.

BMC pulmonary medicine
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a severe lung condition, and finding better ways to diagnose and treat the disease is crucial for improving patient outcomes. Our study sought to develop an artificial neural network (ANN) model for ...

The BCPM method: decoding breast cancer with machine learning.

BMC medical imaging
Breast cancer prediction and diagnosis are critical for timely and effective treatment, significantly impacting patient outcomes. Machine learning algorithms have become powerful tools for improving the prediction and diagnosis of breast cancer. The ...

Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models.

Scientific reports
In an era marked by growing global population and climate variability, ensuring food security has become a paramount concern. Rice, being a staple crop for billions of people, requires accurate and timely yield prediction to ensure global food securi...