Latest AI and machine learning research in surveys for healthcare professionals.
Purpose: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic treatment of an intracranial aneurysm also involves risk, hence identifying rupture-prone aneurysms is of substantial clinical importance. This systematic review aims to evaluate the performance of machine learning algo...
In medical image analysis, model predictions can be affected by sensitive attributes, such as race and gender, leading to fairness concerns and potential biases in diagnostic outcomes. To mitigate this, we present a causal modeling framework, which aims to reduce the impact of sensitive attributes on diagnostic predictions. Our approach introduces a novel fairness criterion, \textbf{Diagnosis Fa...
The goal of this work was to compute the semantic similarity among publicly available health survey questions in order to facilitate the standardiza...
Video quality assessment (VQA) is an important processing task, aiming at predicting the quality of videos in a manner highly consistent with human ...
Machine learning systems are increasingly being used in critical decision making such as healthcare, finance, and criminal justice. Concerns around ...
The interpretation of multi-temporal remote sensing imagery is critical for monitoring Earth's dynamic processes-yet previous change detection metho...
Autism Spectrum Disorder (ASD) is a pervasive developmental disorder of the central nervous system, primarily manifesting in childhood. It is charac...
Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multi...
The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV)...
DEtection TRansformer (DETR) has emerged as a promising architecture for object detection, offering an end-to-end prediction pipeline. In practice, ...
Multimodal survival analysis aims to combine heterogeneous data sources (e.g., clinical, imaging, text, genomics) to improve the prediction quality ...
Background High-quality translations of radiology reports are essential for optimal patient care. Because of limited availability of human translators...
Crowdsourcing is a common approach to rapidly annotate large volumes of data in machine learning applications. Typically, crowd workers are compensa...
Vision is one of the essential sources through which humans acquire information. In this paper, we establish a novel framework for measuring image i...
In e-commerce, ranking the search results based on users' preference is the most important task. Commercial e-commerce platforms, such as, Amazon, A...
Measuring User Experience (UX) with questionnaires is essential for developing and improving products. However, no domain-specific standardized UX q...
The rapid advancement of large language models (LLMs) and multimodal learning has transformed digital content creation and manipulation. Traditional...
Currently artificial intelligence (AI)-enabled chatbots are capturing the hearts and imaginations of the public at large. Chatbots that users can bu...
The wireless spectrum's increasing complexity poses challenges and opportunities, highlighting the necessity for real-time solutions and robust data...
Federated Learning (FL) has emerged as a transformative approach in healthcare, enabling collaborative model training across decentralized data sour...