Artificial Intelligence Medical Compendium

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

Showing 2,781 to 2,790 of 167,607 articles

Considerations for Videourodynamics and How it Impacts Practice.

Neurourology and urodynamics
AIMS: Provide urologists with a comprehensive understanding to guide the optimal and evidence-based utilization of VUDS in contemporary practice. read more 

Robust Quantum Reservoir Learning for Molecular Property Prediction.

Journal of chemical information and modeling
Machine learning has been increasingly utilized in the field of biomedical research to accelerate the drug discovery process. In recent years, the emergence of quantum computing has led to the extensive exploration of quantum machine learning algorit... read more 

T2UE: Generating Unlearnable Examples from Text Descriptions

arXiv
Large-scale pre-training frameworks like CLIP have revolutionized multimodal learning, but their reliance on web-scraped datasets, frequently containing private user data, raises serious concerns about misuse. Unlearnable Examples (UEs) have emerge... read more 

Longitudinal big biological data in the AI era.

Molecular systems biology
Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. ... read more 

Zero Shot Domain Adaptive Semantic Segmentation by Synthetic Data Generation and Progressive Adaptation

arXiv
Deep learning-based semantic segmentation models achieve impressive results yet remain limited in handling distribution shifts between training and test data. In this paper, we present SDGPA (Synthetic Data Generation and Progressive Adaptation), a... read more 

The future of anesthesia education: incorporating technology for safer practices.

Current opinion in anaesthesiology
PURPOSE OF REVIEW: Although effective patient safety education is critical to reducing medical errors, little guidance exists on best practices for patient safety curricula. This review explores the current state of patient safety education in anesth... read more 

Adversarial Attention Perturbations for Large Object Detection Transformers

arXiv
Adversarial perturbations are useful tools for exposing vulnerabilities in neural networks. Existing adversarial perturbation methods for object detection are either limited to attacking CNN-based detectors or weak against transformer-based detecto... read more 

Language as Cost: Proactive Hazard Mapping using VLM for Robot Navigation

arXiv
Robots operating in human-centric or hazardous environments must proactively anticipate and mitigate dangers beyond basic obstacle detection. Traditional navigation systems often depend on static maps, which struggle to account for dynamic risks, s... read more 

Toward Verifiable Misinformation Detection: A Multi-Tool LLM Agent Framework

arXiv
With the proliferation of Large Language Models (LLMs), the detection of misinformation has become increasingly important and complex. This research proposes an innovative verifiable misinformation detection LLM agent that goes beyond traditional t... read more 

Token-Level Precise Attack on RAG: Searching for the Best Alternatives to Mislead Generation

arXiv
While large language models (LLMs) have achieved remarkable success in providing trustworthy responses for knowledge-intensive tasks, they still face critical limitations such as hallucinations and outdated knowledge. To address these issues, the r... read more