AIMC Topic: Humans

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Energy-efficient communication between IoMT devices and emergency vehicles for improved patient care.

PloS one
The rising integration of emergency healthcare services with the Internet of Medical Things (IoMT) creates a significant opportunity to improve real-time communication between patients and emergency vehicles like ambulances. Fast and reliable data in...

Generative AI and academic scientists in US universities: Perception, experience, and adoption intentions.

PloS one
The integration of generative Artificial Intelligence (AI) into academia has sparked interest and debate among academic scientists. This paper explores the early adoption and perceptions of US academic scientists regarding the use of generative AI in...

Optimizing ensemble machine learning models for accurate liver disease prediction in healthcare.

PloS one
Liver disease encompasses a range of conditions affecting the liver, including hepatitis, cirrhosis, fatty liver, and liver cancer. It can be caused by infections, alcohol abuse, obesity, or genetic factors, and it often progresses silently until adv...

Machine learning-based identification of diagnostic and prognostic mitotic cell cycle genes in hepatocellular carcinoma.

PloS one
Mitotic cell cycle (MCC) is a critical process in cell growth and division, and dysregulation of MCC genes may contribute to tumorigenesis. In this study, to identify diagnostic and prognostic value of MCC genes, differentially expressed MCC genes be...

Sulfur as a proxy for identifying coast-inland human mobility in Northern Iberia during Late Prehistory.

PloS one
Population movements constitute a significant driver of cultural change in prehistoric societies. In recent years, sulfur isotopes have emerged as a valuable approach for distinguishing human/animal provenance. However, the scarcity of sulfur isotope...

Deep Unfolded Variable Projection Networks.

International journal of neural systems
In this paper, we present a hybrid learning framework that integrates two model-driven AI paradigms: Deep unfolding and Variable Projections (VPs). The core idea is to unfold the iterations of VP solvers for separable nonlinear least squares (SNLLS) ...

Ecological and carcinogenic risk assessment of potentially toxic elements in rangelands and croplands around Lake Junin (Peru): Integrating remote sensing, machine learning, and land cover segmentation.

The Science of the total environment
The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial dis...

Knowledge and Structure-Based Drug Design of 15-PGDH Inhibitors.

Journal of medicinal chemistry
PGE2 plays important roles in immune cell function and in potentiating tissue regeneration. 15-PGDH is the key enzyme involved in inactivation of PGE2 and its inhibition therefore provides valuable therapeutic opportunity. We have solved the first co...

Human Microbiome-Based Prediction of Health Effects of Foods via Machine Learning.

Journal of agricultural and food chemistry
Food absorption is dependent on the activities of internal microorganisms. When exploring food functionality, considering the food compounds and their metabolites produced by microbial metabolism is crucial. In this study, we developed a machine lear...

Bioinspired adaptive response speed for high-quality human-robot interactions.

Science advances
In human-robot interaction (HRI), the quality of user experience is paramount. Thus, developing strategies to tailor robotic responsiveness to user comfort zone is essential. However, current methods remain constrained by complex software and limited...