Latest AI and machine learning research in universal precautions for healthcare professionals.
The Segment Anything Model (SAM) is a powerful foundation model for image segmentation, showing robust zero-shot generalization through prompt engineering. However, relying on manual prompts is impractical for real-world applications, particularly in scenarios where rapid prompt provision and resource efficiency are crucial. In this paper, we propose the Automation of Prompts for SAM (AoP-SAM), ...
Semi-Supervised Instance Segmentation (SSIS) involves classifying and grouping image pixels into distinct object instances using limited labeled data. This learning paradigm usually faces a significant challenge of unstable performance caused by noisy pseudo-labels of instance categories and pixel masks. We find that the prevalent practice of filtering instance pseudo-labels assessing both class...
The analysis and individual interpretation of hepatitis serology test results is a complex task in laboratory medicine, requiring either experienced p...
In the dentistry field, dental caries is a common issue affecting all age groups. The presence of dental braces and dental restoration makes the detec...
OBJECTIVE: This study aimed to develop machine learning (ML) models to predict HIV status and assessed the factors associated with HIV infection among...
Anomaly detection methods in time series data can play a pivotal role in epidemic surveillance Early Warning Systems (EWS). Statistical and rules-base...
Face anti-spoofing (FAS) is crucial for protecting facial recognition systems from presentation attacks. Previous methods approached this task as a ...
To perform accurate computer vision quality assessments of sperm used within reproductive medicine, a clear separation of each sperm component from th...
The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health...
We developed an AI-driven software solution to quantify metastatic bone disease from WB-DWI scans. Core technologies include: (i) a weakly-supervise...
Recently, the application of deep learning in image colorization has received widespread attention. The maturation of diffusion models has further a...
Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity and mortality, especially among patients requiring ...
Detection of pathogens is a major concern in many fields like medicine, pharmaceuticals, or agri-food. Most conventional detection methods require ski...
This study aimed to develop a predictive model to classify and rank highly active compounds that inhibit HIV-1 integrase (IN). : A total of 2271 pote...
Masked image modeling is one of the most poplular objectives of training. Recently, the SparK model has been proposed with superior performance amon...
Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein ...
This work presents a novel machine learning and signal processing framework designed to consistently detect, localize, and rate facial anomalies such ...
BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence h...
Retroviruses such as HIV cause significant diseases in humans and other organisms, making the discovery of antiretroviral (ARV) drugs a critical prior...
Identifying host defense peptides (HDPs) that are effective against drug-resistant infections is challenging due to their vast sequence space. Artific...