Latest AI and machine learning research in universal precautions for healthcare professionals.
Nucleic-acid biosensors have emerged as useful tools for on-farm detection of foodborne pathogens on fresh produce. Such tools are specifically designed to be user-friendly so that a producer can operate them with minimal training and in a few simple steps. However, one challenge in the deployment of these biosensors is delivering precise sample volumes to the biosensor's reaction sites. To addres...
As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rarely offer new insights to assist clinicians in predicting disease prognosis and treatment response. Using longitudinal retinal imaging data, we develo...
Over the past decade, the size of neural network models has gradually increased in both breadth and depth, leading to a growing interest in the applic...
The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to m...
is a critical-class pathogen that shows great resistance to most conventional antibiotics. Hence, it is of utmost importance to search for novel drug...
BACKGROUND: HIV/AIDS remains a major public health challenge, in Sub-Saharan Africa (SSA). In 2020, 16% of people living with HIV did not know their H...
spp. and hepatitis E virus (HEV) are significant foodborne zoonotic pathogens that impact the health of livestock, farmers, and the general public. T...
This paper explores the integration of haptic gloves and virtual reality (VR) environments to enhance industrial training and operational efficiency w...
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus family with high infectivity and pathogenicity and i...
BACKGROUND & AIMS: Various hepatocellular carcinoma (HCC) prediction models have been proposed for patients with chronic hepatitis B (CHB) using clini...
This study introduces a novel deep learning approach for 3D teeth scan segmentation and labeling, designed to enhance accuracy in computer-aided desig...
is a significant pathogen affecting shrimp and crab farming, particularly strains carrying genes associated with acute hepatopancreatic necrosis synd...
The interaction between peptides and major histocompatibility complex (MHC) molecules is pivotal in autoimmunity, pathogen recognition and tumor immun...
Reducing damage and missed harvest rates is essential for improving efficiency in unmanned cabbage harvesting. Accurate real-time segmentation of cabb...
BACKGROUND AND AIMS: This study aims to develop and validate a machine learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepati...
Much of the human genome is transcribed into RNAs, many of which contain structural elements that are important for their function. Such RNA molecules...
BACKGROUND: The age distribution of a mosquito population is a major determinant of its vectorial capacity. To contribute to disease transmission, a c...
BACKGROUND: is widely recognised as a periodontal pathogen. In recent years, there has been growing interest in the use of medicinal plant extracts a...
Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications...
Artificial Intelligence and Machine Learning (AI/ML) techniques, including reverse vaccinology and predictive models, have already been applied for de...