Latest AI and machine learning research in surveys for healthcare professionals.
Evaluating the behavioral boundaries of deep learning (DL) systems is crucial for understanding their reliability across diverse, unseen inputs. Existing solutions fall short as they rely on untargeted random, model- or latent-based perturbations, due to difficulties in generating controlled input variations. In this work, we introduce Mimicry, a novel black-box test generator for fine-grained, ...
Networks are crucial components of many sectors, including telecommunications, healthcare, finance, energy, and transportation.The information carried in such networks often contains sensitive user data, like location data for commuters and packet data for online users. Therefore, when considering data release for networks, one must ensure that data release mechanisms do not leak information abo...
For decades, mainframe systems have been vital in enterprise computing, supporting essential applications across industries like banking, retail, an...
Diffusion models (DMs) have achieved state-of-the-art performance on various generative tasks such as image synthesis, text-to-image, and text-guide...
Multimodal AI models capable of associating images and text hold promise for numerous domains, ranging from automated image captioning to accessibil...
Large language models (LLMs) are now being considered and even deployed for applications that support high-stakes decision-making, such as recruitme...
OBJECTIVES: Our aim was to compare the usability and reliability of answers to clinical questions posed of Chat-Generative Pre-Trained Transformer (Ch...
With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent ...
PROteolysis TArgeting Chimeras (PROTACs) has recently emerged as a promising technology. However, the design of rational PROTACs, especially the linke...
The application of machine learning (ML) in detecting, diagnosing, and treating mental health disorders is garnering increasing attention. Tradition...
Recently, the text-to-image diffusion model has gained considerable attention from the community due to its exceptional image generation capability....
Prostate cancer represents a major threat to health. Early detection is vital in reducing the mortality rate among prostate cancer patients. One app...
Deep learning has achieved impressive performance across various medical imaging tasks. However, its inherent bias against specific groups hinders i...
The rapid advancement of foundation models in medical imaging represents a significant leap toward enhancing diagnostic accuracy and personalized tr...
Vision-language models (VLMs) pre-trained on extensive datasets can inadvertently learn biases by correlating gender information with specific objec...
Recently, electroencephalography (EEG) signals have been actively incorporated to decode brain activity to visual or textual stimuli and achieve obj...
Suicide poses a global health crisis with significant social and economic impact. Prevention may be possible if objective quantitative methods are dev...
The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid ...
Recently, large language models (LLMs) have expanded into various domains. However, there remains a need to evaluate how these models perform when p...
Path planning is a fundamental scientific problem in robotics and autonomous navigation, requiring the derivation of efficient routes from starting ...