AIMC Topic: Neural Networks, Computer

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Neural Signals-Based Respiratory Motion Tracking: A Surface Electromyography Study.

International journal of radiation oncology, biology, physics
PURPOSE: Neural signals-based respiratory motion tracking offers a potential solution to the system latency issue of medical linear accelerators in respiratory motion tracking radiation therapy. However, decoding respiratory-related neural signals fr...

Boosted neural network modeling of psychological and social factors of work affecting safety performance and job satisfaction in the process industry.

BMC psychology
Psychological and social factors of work were found to influence workers' safety performance and job satisfaction. This study aimed to assess the effects of psychological and social factors of work affecting safety performance and job satisfaction of...

A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning.

Scientific reports
In this study, serum Raman spectra are introduced into the screening of schizophrenia. We collect serum Raman spectra from schizophrenic and healthy individuals, classified them based on four convolutional neural networks, and developed an assisted s...

Daily insider threat detection with hybrid TCN transformer architecture.

Scientific reports
Internal threats are becoming more common in today's cybersecurity landscape. This is mainly because internal personnel often have privileged access, which can be exploited for malicious purposes. Traditional detection methods frequently fail due to ...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Virology journal
Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a chronic disease with limited impact on life expectancy. However, people living with HIV(PLWHs) faced high critical illness risk due to the increased pr...

Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images.

Scientific reports
Kidney cancer is a leading cause of cancer-related mortality, with renal cell carcinoma (RCC) being the most prevalent form, accounting for 80-85% of all renal tumors. Traditional diagnosis of kidney cancer requires manual examination and analysis of...

A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis.

Scientific reports
Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). This field aims to enable computers to analyze, comprehend, and generate human lan...

PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context.

Nature communications
Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenici...

Limits on the computational expressivity of non-equilibrium biophysical processes.

Nature communications
Many biological decision-making tasks require classifying high-dimensional chemical states. The biophysical and computational mechanisms that enable classification remain enigmatic. In this work, using Markov jump processes as an abstraction of gener...

Retinal image-based disease classification using hybrid deep architecture with improved image features.

International ophthalmology
OBJECTIVE: Ophthalmologists use retinal fundus imaging as a useful tool to diagnose retinal issues. Recently, research on machine learning has concentrated on disease diagnosis. However, disease detection is less accurate, more likely to be misidenti...