Latest AI and machine learning research in cultural competence for healthcare professionals.
Machine learning courses often use pre-labeled datasets, hiding the subjectivity of human annotation. This creates students with an overly trusting view of AI data and models, undervaluing interpretive diversity. We investigated whether manual data annotation tasks teach students about subjective labeling. Study Design: An annotation activity was implemented at two universities: Fontys (Netherla...
The genus Pseudomonas consists of diverse and ecologically significant species that form close associations with both plants and animals. This genus is widely studied due to the clinically relevant Pseudomonas aeruginosa, model plant pathogen Pseudomonas syringae, and non-pathogenic, industrially relevant Pseudomonas putida. The different metabolic and physiological capabilities of these species a...
Key regulators of neural network activity in multiple advanced cognitive processes and essential components of the blood-brain barrier, astrocytes con...
Industrial anomaly detection aims to identify and localize defective regions without relying on exhaustive annotations of all possible defect types. A...
Text-to-image (T2I) models can synthesize realistic, prompt-aligned images, yet samples generated for the same prompt often cover only a small subset ...
Recent advances in Vision-Language Models (VLMs) have significantly improved image geo-localization, yet existing models remain susceptible to landmar...
Long COVID (LC) affects millions of individuals worldwide, particularly those with preexisting comorbidities. However, whether these comorbidities sho...
Foundation models such as CLIP have enabled open-vocabulary object detectors that generalise to novel categories via vision-language similarity. Howev...
Raw images inherently suffer from noise due to the stochastic nature of light and sensor hardware imperfections. As real photon counts fall, the ratio...
While diffusion models achieve state-of-the-art image quality for text-to-image (T2I) generation, recent work has demonstrated that they suffer from s...
Purpose The application of machine learning (ML) to osteoporosis prediction has expanded rapidly, yet no comprehensive meta-analysis has synthesized t...
Many insects manipulate plants by injecting effector proteins. In one extreme example of this molecular "hijacking", Hormaphis cornu aphids inject bic...
Text-to-image (T2I) models have been shown to exhibit social biases. Prior work has mainly focused on gender, skin tone, and cultural representation w...
Large vision-language models incur substantial inference costs because high-resolution inputs introduce thousands of visual tokens, many of which are ...
Subject-driven personalized text-to-image generation requires a pretrained diffusion model to acquire a specific subject from a few reference images w...
This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned ...
Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain...
Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assu...
Diffusion models achieve impressive image-generation quality but remain expensive at inference time. Diffusion distillation reduces sampling steps, ye...
Background: The hyperplasia and dysplasia stage (pre-cancer) offers a viable opportunity to reduce the incidence and mortality of oral cancer through ...