Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 3,471 to 3,480 of 168,679 articles

Beyond the Conveyor Belt: The Influence of Robotization on Work Characteristics. A Qualitative Study in Manufacturing Companies.

The Spanish journal of psychology
The numbers of robots in organizations grow at an increasing rate. However, very little is known about how robotization (i.e., the implementation of robots at work) affects the work characteristics of the jobs it impacts. This qualitative study focus... read more 

FinMMR: Make Financial Numerical Reasoning More Multimodal, Comprehensive, and Challenging

arXiv
We present FinMMR, a novel bilingual multimodal benchmark tailored to evaluate the reasoning capabilities of multimodal large language models (MLLMs) in financial numerical reasoning tasks. Compared to existing benchmarks, our work introduces three... read more 

Toward automated assessment of conjunctival hyperemia: A semisupervised artificial intelligence approach.

Annals of the New York Academy of Sciences
This paper develops an automated approach for conjunctival hyperemia grading from slit-lamp images using semisupervised learning. We conducted a retrospective study including slit-lamp images from two study sites. Two independent graders assessed the... read more 

Single cell density prediction based on optically induced electrokinetics (OEK) and machine learning.

Analytical methods : advancing methods and applications
Single cell density is a key indicator for judging cell physiological state, crucial for studying cell function. However, existing measurement methods are often complex and time-consuming, limiting their efficiency in practical applications. To addre... read more 

PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers

arXiv
Multivariate time-series classification is pivotal in domains ranging from wearable sensing to biomedical monitoring. Despite recent advances, Transformer- and CNN-based models often remain computationally heavy, offer limited frequency diversity, ... read more 

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.

Scientific reports
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud... read more 

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.

Scientific reports
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t... read more 

Benchmarking Uncertainty and its Disentanglement in multi-label Chest X-Ray Classification

arXiv
Reliable uncertainty quantification is crucial for trustworthy decision-making and the deployment of AI models in medical imaging. While prior work has explored the ability of neural networks to quantify predictive, epistemic, and aleatoric uncerta... read more 

Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1:  = 17... read more 

A Few Words Can Distort Graphs: Knowledge Poisoning Attacks on Graph-based Retrieval-Augmented Generation of Large Language Models

arXiv
Graph-based Retrieval-Augmented Generation (GraphRAG) has recently emerged as a promising paradigm for enhancing large language models (LLMs) by converting raw text into structured knowledge graphs, improving both accuracy and explainability. Howev... read more