AIMC Topic: Humans

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Stylometry can reveal artificial intelligence authorship, but humans struggle: A comparison of human and seven large language models in Japanese.

PloS one
The purpose of this study was to estimate the artificial intelligence (AI) detection potential using stylometric analysis in Study 1 and examine the AI detection abilities of humans in Study 2. In Study 1, we compared 100 human-written public comment...

Multimodal emotion recognition via adaptive high-order transforme network.

PloS one
Multimodal emotion recognition leverages multiple modalities to capture emotional cues more comprehensively, thereby improving the accuracy and robustness of emotion recognition. From the perspective of multimodal data and feature learning, reducing ...

Use of machine learning for early prediction of short-term mortality in veterans with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...

Comparison of serum lactate and lactate-derived ratios as prognostic biomarkers in pediatric dengue shock syndrome using supervised machine learning models.

PloS one
BACKGROUND: Dengue shock syndrome (DSS), with critical complications encompassing mechanical ventilation (MV), dengue-associated acute liver failure (PALF), and encephalitis, is associated with high mortality in children. Although serum lactate is a ...

Extended Directed Fuzzy Social Network Analysis: A framework and application to curriculum networks in Chinese vocational education.

PloS one
Due to the differences in node types and the diversity of network relationships, Fuzzy Social Network Analysis (FSNA) needs to specifically address the issues of network heterogeneity and relationship ambiguity. To address this challenge, we propose ...

Dual-branch differential channel hypergraph convolutional network for human skeleton based action recognition.

PloS one
Graph Convolutional Networks (GCNs) perform well in skeleton action recognition tasks, but their pairwise node connections make it difficult to effectively model high-order dependencies between non-adjacent joints. To address this issue, hypergraph m...

Machine learning reveals distinct T-cell receptor clusters in plasma cell dyscrasias compared to healthy controls.

PloS one
T-cell receptor (TCR) repertoire diversity has been implicated in the progression and prognosis of multiple myeloma (MM). This study aimed to evaluate the association between T-cell clonality, immune response, and clinical outcomes in patients with p...

A HAZOP-based hazard identification model for urban gas accidents: Development and empirical validation.

PloS one
Urban gas accidents pose significant threats to public safety and urban infrastructure, with traditional hazard identification methods often relying on manual inspections and experience-based judgments, leading to incomplete or inconsistent results. ...

Revolutionizing cervical cancer care: the synergistic effects of hyperthermia and machine learning.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
OBJECTIVE: This study aimed to examine the impact of hyperthermia in conjunction with concurrent chemoradiotherapy (CCRT) on peripheral immune markers in patients with locally advanced cervical cancer (LACC). Additionally, we sought to predict the as...

Intelligent Gait Analysis System Enabled by Liquid Metal-Embedded Sponge Triboelectric Sensor Arrays.

ACS applied materials & interfaces
Gait dynamics are pivotal biomarkers for early disease prediction and human health assessment. In this study, we propose an intelligent monitoring system that integrates flexible PDMS/liquid metal sponge triboelectric nanogenerator (PLMFT) arrays wit...