AIMC Topic: Humans

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The impact of artificial intelligence on corporate green innovation: Can "increasing quantity" and "improving quality" go hand in hand?

Journal of environmental management
In the current era of digitalization and greenization, it is of great importance to explore how enterprises utilize artificial intelligence (AI) to promote green innovation. This paper explores the green innovation effects of AI and its underlying me...

Single-Cell Array Enhanced Cell Damage Recognition Using Artificial Intelligence for Anticancer Drug Discovery.

Analytical chemistry
This work developed a cell damage recognition method based on single-cell arrays using an artificial intelligence tool. The method uses micropatterns (single-cell micropatches and microwells) to isolate each cell in an ordered array to minimize cell ...

An Enhanced Protocol to Expand Human Exposome and Machine Learning-Based Prediction for Methodology Application.

Environmental science & technology
The human exposome remains limited due to the challenging analytical strategies used to reveal low-level endocrine-disrupting chemicals (EDCs) and their metabolites in serum and urine. This limits the integrity of the EDC exposure assessment and hind...

Machine learning-enhanced surface-enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta.

Proceedings of the National Academy of Sciences of the United States of America
The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, polycyclic aromatic compounds (PACs), are essential for environmental and health monitoring, for assessing toxicological exposure and their associated ...

AI-generated and doctors' answers to health-related questions.

Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke
BACKGROUND: Several studies have investigated how large language models answer health-related questions. In a study from 2023, responses to health-related questions in English generated by the language model GPT-3.5 were perceived as more empathetic ...

Decision Fusion-Based Deep Learning for Channel State Information Channel-Aware Human Action Recognition.

Sensors (Basel, Switzerland)
WiFi channel state information (CSI) has emerged as a promising modality for human action recognition due to its non-invasive nature and robustness in diverse environments. However, most existing methods process CSI channels collectively, potentially...

Research on Upper Limb Motion Intention Classification and Rehabilitation Robot Control Based on sEMG.

Sensors (Basel, Switzerland)
sEMG is a non-invasive biomedical engineering technique that can detect and record electrical signals generated by muscles, reflecting both motor intentions and the degree of muscle contraction. This study aims to classify and recognize nine types of...

CLUMM: Contrastive Learning for Unobtrusive Motion Monitoring.

Sensors (Basel, Switzerland)
Traditional approaches for human monitoring and motion recognition often rely on wearable sensors, which, while effective, are obtrusive and cause significant discomfort to workers. More recent approaches have employed unobtrusive, real-time sensing ...

Machine Learning-Enabled Non-Invasive Screening of Tumor-Associated Circulating Transcripts for Early Detection of Colorectal Cancer.

International journal of molecular sciences
Colorectal cancer (CRC) is a major cause of cancer-related mortality, highlighting the need for accurate and non-invasive diagnostics. This study assessed the utility of tumor-associated circulating transcripts (TACTs) as biomarkers for CRC detection...