Latest AI and machine learning research in hiv/aids for healthcare professionals.
The ubiquity of machine learning, particularly deep learning, applied to graphs is evident in applications ranging from cheminformatics (drug discovery) and bioinformatics (protein interaction prediction) to knowledge graph-based query answering, fraud detection, and social network analysis. Concurrently, graph data management deals with the research and development of effective, efficient, scal...
Recent advances in deep learning have shown that learning robust feature representations is critical for the success of many computer vision tasks, including medical image segmentation. In particular, both transformer and convolutional-based architectures have benefit from leveraging pretext tasks for pretraining. However, the adoption of pretext tasks in 3D medical imaging has been less explore...
Processing-using-DRAM (PUD) is a paradigm where the analog operational properties of DRAM structures are used to perform bulk logic operations. Whil...
Individuals who are differently-able in vision cannot proceed with their day-to-day activities as smoothly as other people do. Especially independen...
Transformer-based Super-Resolution (SR) methods have demonstrated superior performance compared to convolutional neural network (CNN)-based SR appro...
Appropriate identification of burn depth and size is paramount. Despite the development of burn depth assessment aids [eg, laser Doppler imaging (LDI)...
A fundamental challenge in artificial intelligence involves understanding the cognitive mechanisms underlying visual reasoning in sophisticated mode...
Recently, map representations based on radiance fields such as 3D Gaussian Splatting and NeRF, which excellent for realistic depiction, have attract...
Fine-tuning a large language model (LLM) using the local data of edge users can enable personalized services and applications. For privacy protectio...
To restore proper blood flow in blocked coronary arteries via angioplasty procedure, accurate placement of devices such as catheters, balloons, and ...
A mental health disorder is a clinically significant impairment in a persons intellect, emotional control, or behavior. Mental disorders and outpati...
The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often st...
LLMs are tuned to follow instructions (aligned) by learning which of two outputs users prefer for a prompt. However, this preference data format doe...
Despite coronary artery calcium scoring being considered a largely solved problem within the realm of medical artificial intelligence, this paper ar...
The proliferation of misinformation on social media platforms has highlighted the need to understand how individual personality traits influence sus...
Object removal has so far been dominated by the mask-and-inpaint paradigm, where the masked region is excluded from the input, leaving models relyin...
We study image segmentation in the biological domain, particularly trait and part segmentation from specimen images (e.g., butterfly wing stripes or...
The inference of large-sized images on Internet of Things (IoT) devices is commonly hindered by limited resources, while there are often stringent l...
Recent self-supervised learning (SSL) models trained on human-like egocentric visual inputs substantially underperform on image recognition tasks co...
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on...