Latest AI and machine learning research in hiv/aids for healthcare professionals.
Transformer-based architectures have revolutionized the landscape of deep learning. In computer vision domain, Vision Transformer demonstrates remarkable performance on par with or even surpassing that of convolutional neural networks. However, the quadratic computational complexity of its self-attention mechanism poses challenges for classical computing, making model training with high-dimensio...
Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces challenges in efficient information retrieval and analysis, especially from unstructured sources like news, presenting a need for innovative tools. Methodology: The study introduces SCANAR and AIDOC, open-source Python-based tools designed to improve hori...
The development of artificial intelligence (AI) including generative large language models (LLMs) and software like ChatGPT is likely to significantly...
Artificial Intelligence (AI) is revolutionizing various fields, including scientific writing, which traditionally relies on human intellectual effort....
INTRODUCTION: Optimal use of HIV testing resources accelerates progress towards ending HIV as a global threat. In Kenya, current testing practices yie...
Prior work using Masked Autoencoders (MAEs) typically relies on random patch masking based on the assumption that images have significant redundanci...
Imbalanced data represent a distribution with more frequencies of one class (majority) than the other (minority). This phenomenon occurs across vari...
Recent advancements in Large Language Models (LLMs) have marked significant progress in understanding and responding to medical inquiries. However, ...
The fusion of Large Language Models with vision models is pioneering new possibilities in user-interactive vision-language tasks. A notable applicat...
By 2050, a quarter of the US population will be over the age of 65 with greater than a 40% risk of developing life-altering neuromusculoskeletal pat...
Generative machine learning models for small molecule drug discovery have shown immense promise, but many molecules they generate are too difficult ...
Visual Question Answering (VQA) models, which fall under the category of vision-language models, conventionally execute multiple downsampling proces...
Vision-Language Models (VLMs) based on Mixture-of-Experts (MoE) architectures have emerged as a pivotal paradigm in multimodal understanding, offeri...
Reconstructing three-dimensional (3D) structures from two-dimensional (2D) X-ray images is a valuable and efficient technique in medical application...
Advances in large language models (LLMs) offer new possibilities for enhancing math education by automating support for both teachers and students. ...
Current Visual Simultaneous Localization and Mapping (VSLAM) systems often struggle to create maps that are both semantically rich and easily interp...
Lung cancer has the highest rate of cancer-caused deaths, and early-stage diagnosis could increase the survival rate. Lung nodules are common indica...
Rapid generation of large-scale orthoimages from Unmanned Aerial Vehicles (UAVs) has been a long-standing focus of research in the field of aerial m...
Real-world low-light images captured by imaging devices suffer from poor visibility and require a domain-specific enhancement to produce artifact-fr...
BACKGROUND: This study aims to develop and examine the performance of machine learning (ML) algorithms in predicting viral suppression among statewide...