Latest AI and machine learning research in hepatitis for healthcare professionals.
Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the leading members of ESKAPE pathogens, it plays a major role in a wide range of infections that cause pneumonia, urinary tract infections, and bacteremia, especially in immunocompromised and hospitalized patients. The recent increase in multidrug-resis...
Machine learning methods are increasingly applied to analyze health-related public discourse based on large-scale data, but questions remain regarding their ability to accurately detect different types of health sentiments. Especially, Large Language Models (LLMs) have gained attention as a powerful technology, yet their accuracy and feasibility in capturing different opinions and perspectives o...
Vaccine infodemics, driven by misinformation, disinformation, and inauthentic online behaviours, pose significant threats to global public health. T...
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituen...
Vaccination plays a vital role in global public health, yet healthcare professionals often struggle to access immunization guidelines quickly and ef...
Rice leaf diseases significantly reduce productivity and cause economic losses, highlighting the need for early detection to enable effective manage...
6D pose estimation of rigid objects is a long-standing and challenging task in computer vision. Recently, the emergence of deep learning reveals the p...
BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chro...
BACKGROUND AND AIMS: Liver biopsy is the gold standard for assessing fibrosis in cirrhotic livers, yet cirrhosis is spatially heterogeneous and contin...
Accurately and efficiently estimating the cortical thickness from magnetic resonance images (MRIs) is crucial for neuroscientific studies and clinical...
Comorbidity networks, which capture disease-disease co-occurrence usually based on electronic health records, reveal structured patterns in how dise...
The rapid advancement of 3D vision-language models (VLMs) has spurred significant interest in interactive point cloud processing tasks, particularly...
In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error experimentation and extensive in vivo testing, oft...
Claims made by individuals or entities are oftentimes nuanced and cannot be clearly labeled as entirely "true" or "false" -- as is frequently the ca...
Recurrent waves of viral infection necessitate vaccines and therapeutics that remain effective against emerging viruses. Our ability to evaluate inter...
The use of applications on computers, smartphones, and tablets has been considerably simplified thanks to interactive and dynamic graphical interfac...
The use of applications on computers, smartphones, and tablets has been considerably simplified thanks to interactive and dynamic graphical interfac...
Leveraging the powerful generation capability of large-scale pretrained text-to-image models, training-free methods have demonstrated impressive ima...
Adeno-associated virus (AAV) is a non-enveloped DNA virus infecting a wide variety of species, tissues, and cell types, which is recognized as a safe ...
BACKGROUND: Cirrhosis is a leading cause of morbidity and mortality worldwide, yet preventable at early stages. Currently, effective approaches for ea...