Latest AI and machine learning research in surveys for healthcare professionals.
Facial recognition technology (FRT) is increasingly used in criminal investigations, yet most evaluations of its accuracy rely on high-quality images, unlike those often encountered by law enforcement. This study examines how five common forms of image degradation--contrast, brightness, motion blur, pose shift, and resolution--affect FRT accuracy and fairness across demographic groups. Using syn...
Popularity bias occurs when popular items are recommended far more frequently than they should be, negatively impacting both user experience and recommendation accuracy. Existing debiasing methods mitigate popularity bias often uniformly across all users and only partially consider the time evolution of users or items. However, users have different levels of preference for item popularity, and t...
Multilingual vision-language models promise universal image-text retrieval, yet their social biases remain under-explored. We present the first syst...
Supervised pretrained models have become widely used in deep learning, especially for image segmentation tasks. However, when applied to specialized...
Deep learning models often achieve high performance by inadvertently learning spurious correlations between targets and non-essential features. For ...
In Human-Robot Interaction, speech is one of the most intuitive and effective communication channel. In Industry 4.0, speech-based communication can s...
We introduce $\textit{Backward Conformal Prediction}$, a method that guarantees conformal coverage while providing flexible control over the size of...
How discriminative position information is for image classification depends on the data. On the one hand, the camera position is arbitrary and objec...
AI-enhanced personality assessments are increasingly shaping hiring decisions, using affective computing to predict traits from the Big Five (OCEAN)...
Algorithmic bias has been the subject of much recent controversy. To clarify what is at stake and to make progress resolving the controversy, a bett...
Automatic Speech Recognition (ASR) technologies have transformed human-computer interaction; however, low-resource languages in Africa remain signif...
Imagine hearing a dog bark and turning toward the sound only to see a parked car, while the real, silent dog sits elsewhere. Such sensory conflicts ...
Deep vision models often rely on biases learned from spurious correlations in datasets. To identify these biases, methods that interpret high-level,...
Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cance...
Recent advances in image-based saliency prediction are approaching gold standard performance levels on existing benchmarks. Despite this success, we...
Edge computing, with its low latency, dynamic scalability, and location awareness, along with the convergence of computing and communication paradig...
Large Language Models (LLMs) have gained significant popularity among healthcare professionals as tools for AI-driven interactions. These models can a...
This paper investigates the development and evaluation of a chatbot for administering the EQ5D questionnaire with a focus on improving user experience...
The rise of artificial intelligence (AI) in medical care presents several opportunities, including improving patient outcomes. As part of the PEAK pro...
In the past decade, extended reality (XR) has been introduced into healthcare due to several potential benefits, such as scalability and cost savings....