AIMC Topic: Humans

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PIRNet: Personality-Enhanced Iterative Refinement Network for Emotion Recognition in Conversation.

IEEE transactions on neural networks and learning systems
Emotion recognition in conversation (ERC) is important for enhancing user experience in human-computer interaction. Unlike vanilla emotion recognition in individual utterances, ERC aims to classify constituent utterances in a dialog into correspondin...

ADGAN: Attribute-Driven Generative Adversarial Network for Synthesis and Multiclass Classification of Pulmonary Nodules.

IEEE transactions on neural networks and learning systems
Lung cancer is the leading cause of cancer-related deaths worldwide. According to the American Cancer Society, early diagnosis of pulmonary nodules in computed tomography (CT) scans can improve the five-year survival rate up to 70% with proper treatm...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

IEEE transactions on neural networks and learning systems
Early time series classification predicts the class label of a given time series before it is completely observed. In time-critical applications, such as arrhythmia monitoring in ICU, early treatment contributes to the patient's fast recovery, and ea...

Exploring the eating experience of a pneumatically-driven edible robot: Perception, taste, and texture.

PloS one
This study investigated the effects of animated food consumption on human psychology. We developed a movable, edible robot and evaluated the participants' impressions induced by the visualization of its movements and eating of the robot. Although sev...

A Novel Multi-Scale Graph Neural Network for Metabolic Pathway Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Predicting the metabolic pathway classes of compounds in the human body is an important problem in drug research and development. For this purpose, we propose a Multi-Scale Graph Neural Network framework, named MSGNN. The framework includes a subgrap...

The association between vitamin D deficiency and the clinical outcomes of hospitalized COVID-19 patients.

F1000Research
BACKGROUND: Vitamin D deficiency is an emerging public health problem that affects more than one billion people worldwide. Vitamin D has been shown to be effective in preventing and reducing the severity of viral respiratory diseases, including influ...

Synchronous Mutual Learning Network and Asynchronous Multi-Scale Embedding Network for miRNA-Disease Association Prediction.

Interdisciplinary sciences, computational life sciences
MicroRNA (miRNA) serves as a pivotal regulator of numerous cellular processes, and the identification of miRNA-disease associations (MDAs) is crucial for comprehending complex diseases. Recently, graph neural networks (GNN) have made significant adva...

Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study.

International journal of medical informatics
BACKGROUND: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing...

Enhanced Noise-Resilient Pressure Mat System Based on Hyperdimensional Computing.

Sensors (Basel, Switzerland)
Traditional systems for indoor pressure sensing and human activity recognition (HAR) rely on costly, high-resolution mats and computationally intensive neural network-based (NN-based) models that are prone to noise. In contrast, we design a cost-effe...