AIMC Topic: Humans

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Cognition-enhanced geospatial decision framework integrating fuzzy FCA, surprisingly popular method, and a large language model.

Scientific reports
This study introduces a cognition-enhanced framework for geospatial decision-making by integrating Fuzzy Formal Concept Analysis (FCA), the Surprisingly Popular (SP) method, and a Large Language Model (GPT-4o). Our approach captures cognitive influen...

Clustering cell nuclei on microgrooves for disease diagnosis using deep learning.

Scientific reports
Various diseases including laminopathies and certain types of cancer are associated with abnormal nuclear mechanical properties that influence cellular and nuclear deformations in complex environments. Recently, microgroove substrates designed to mim...

Associations between weight gain, integrase inhibitors antiretroviral agents, and gut microbiome in people living with HIV: a cross-sectional study.

Scientific reports
Dolutegravir and bictegravir are second-generation HIV integrase strand transfer inhibitors (INSTIs) that were previously associated with abnormal weight gain. This monocentric cross-sectional study investigates associations between weight gain durin...

Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems.

Scientific reports
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...

Automated grading of rectocele with an MRI radiomics model.

Scientific reports
To develop an automated grading model for rectocele (RC) based on radiomics and evaluate its efficacy. This study retrospectively analyzed a total of 9,392 magnetic resonance imaging (MRI) images obtained from 222 patients who underwent dynamic magne...

Attentional responses in toddlers: A protocol for assessing the impact of a robotic animated animal and a real dog.

PloS one
BACKGROUND: Attentional processes in toddlers are characterized by a state of alertness in which they focus their waking state for short periods. It is essential to develop assessment and attention stimulation protocols from an early age to improve t...

Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning.

PloS one
In open environments, complex and variable backgrounds and dense multi-scale targets are two key challenges for crowd counting. Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in comp...

Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval.

PloS one
Text classification plays an essential role in natural language processing and is commonly used in tasks like categorizing news, sentiment analysis, and retrieving relevant information. [0pc][-9pc]Please check and confirm the inserted city and countr...

The design of consumer behavior prediction and optimization model by integrating DQN and LSTM.

PloS one
Amidst the rapid evolution of e-commerce and the growing abundance of consumer shopping data, accurately identifying consumer interests and enabling targeted outreach has become a critical focus for merchants and researchers. This study introduces th...

Understanding dimensions of trust in AI through quantitative cognition: Implications for human-AI collaboration.

PloS one
Human-AI collaborative innovation relies on effective and clearly defined role allocation, yet empirical research in this area remains limited. To address this gap, we construct a cognitive taxonomy trust in AI framework to describe and explain its i...