AIMC Topic: Humans

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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...

Physically grounded deep learning-enabled gold nanoparticle localization and quantification in photonic resonator absorption microscopy for digital resolution molecular diagnostics.

Biosensors & bioelectronics
Accurate molecular biomarker detection with digital-resolution sensitivity is essential for applications such as disease diagnostics, therapeutic studies, and biomedical research. Here, we present LOCA-PRAM (LOcalization with Context Awareness), a de...

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition.

Neural networks : the official journal of the International Neural Network Society
Neuroscience shows that the brain stimulated by external information can induce functional responses to emotions, which can be measured and analyzed by electroencephalogram (EEG). Most existing works focus on extracting specific spatial topological i...

Compact CNN module balancing between feature diversity and redundancy.

Neural networks : the official journal of the International Neural Network Society
Feature diversity and redundancy play a crucial role in enhancing a model's performance, although their effect on network design remains underexplored. Herein, we introduce BDRConv, a compact convolutional neural network (CNN) module that establishes...

Artificial intelligence-driven integration of multi-omics and radiomics: A new hope for precision cancer diagnosis and prognosis.

Biochimica et biophysica acta. Molecular basis of disease
Despite advances in cancer diagnosis and treatment, the disease remains a major health challenge. Integrating multi-omics, radiomics, and artificial intelligence has improved detection, prognosis, and treatment monitoring. Molecular multi-omics provi...

Event-triggered control for input-constrained nonzero-sum games through particle swarm optimized neural networks.

Neural networks : the official journal of the International Neural Network Society
To accommodate the increasing system scale, improve the system operation success rate and save the computational and communication resources, it is urgent to obtain the Nash equilibrium solution for systems with increasing controllers in an effective...

Comprehensive analyses: Using machine learning models for mortality prediction in the intensive care unit of internal medicine.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research
Mortality prediction in the intensive care unit (ICU) is essential in patient management. Emerging methods such as machine learning (ML) can be employed to predict ICU patients' mortality. Patients receiving treatment in the ICU of the internal medic...

Comparison of Ground Reaction Forces and Net Joint Moment Predictions: Skeletal Model Versus Artificial Neural Network-Based Approach.

Journal of applied biomechanics
Artificial neural networks (ANNs) are becoming a regular tool to support biomechanical methods, while physics-based models are widespread to understand the mechanics of body in motion. Thus, this study aimed to demonstrate the accuracy of recurrent A...

Machine Learning-Based Algorithm to Predict Procedural Success in a Large European Cohort of Hybrid Chronic Total Occlusion Percutaneous Coronary Interventions.

The American journal of cardiology
CTOs are frequently encountered in patients undergoing invasive coronary angiography. Even though technical progress in CTO-PCI and enhanced skills of dedicated operators have led to substantial procedural improvement, the success of the intervention...

A coupled machine-learning and sensitivity analysis framework to link dust activity in the Tigris-Euphrates basin to climatic and human-induced drivers.

Environmental research
This study analyzes the impact of climate-related stressors and water resources development in the Tigris-Euphrates basin on regional dust storm intensity and frequency. To this end, we first utilize remote sensing data on Aerosol Optical Depth (AOD)...