AIMC Topic: Humans

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[Nobel Prize in physics 2024 : John J. Hopfield and Geoffrey E. Hinton. From Hopfield and Hinton to AlphaFold: The 2024 Nobel Prize honors the pioneers of deep learning].

Medecine sciences : M/S
On October 8, 2024, the Nobel Prize in Physics was awarded to John J. Hopfield, professor at Princeton University, and Geoffrey E. Hinton, professor at the University of Toronto, for their "fundamental discoveries that made possible machine learning ...

Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Environmental science and pollution research international
Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air pollutants contribute to numerous premature deaths each year. In Europe, and particularly in Poland, air...

Artificial intelligence in chronic kidney disease management: a scoping review.

Theranostics
Chronic kidney disease (CKD) is a major public health problem worldwide associated with cardiovascular disease, renal failure, and mortality. To effectively address this growing burden, innovative solutions to management are urgently required. We co...

Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning.

Frontiers in immunology
BACKGROUND: Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.

The relationship between epigenetic biomarkers and the risk of diabetes and cancer: a machine learning modeling approach.

Frontiers in public health
INTRODUCTION: Epigenetic biomarkers are molecular indicators of epigenetic changes, and some studies have suggested that these biomarkers have predictive power for disease risk. This study aims to analyze the relationship between 30 epigenetic biomar...

Unveiling CNS cell morphology with deep learning: A gateway to anti-inflammatory compound screening.

PloS one
Deciphering the complex relationships between cellular morphology and phenotypic manifestations is crucial for understanding cell behavior, particularly in the context of neuropathological states. Despite its importance, the application of advanced i...

Optimizing deep learning models for glaucoma screening with vision transformers for resource efficiency and the pie augmentation method.

PloS one
Glaucoma is the leading cause of irreversible vision impairment, emphasizing the critical need for early detection. Typically, AI-based glaucoma screening relies on fundus imaging. To tackle the resource and time challenges in glaucoma screening with...

Teleoperator Coupling Dynamics Impact Human Motor Control Across Pursuit Tracking Speeds.

IEEE transactions on haptics
Robotic teleoperators introduce novel electromechanical dynamics between the user and the environment. While considerable effort has focused on minimizing these dynamics, we lack a robust understanding of their impact on user task performance across ...

DT-Transformer: A Text-Tactile Fusion Network for Object Recognition.

IEEE transactions on haptics
Humans rely on multiple senses to understand their surroundings, and so do robots. Current research in haptic object classification focuses on visual-haptic methods, but faces limitations in performance and dataset size. Unlike images, text does not ...

Object Recognition Using Shape and Texture Tactile Information: A Fusion Network Based on Data Augmentation and Attention Mechanism.

IEEE transactions on haptics
Currently, most tactile-based object recognition algorithms focus on single shape or texture recognition. However, these single attribute-based recognition methods perform poorly when dealing with objects with similar shape or texture characteristics...