Latest AI and machine learning research in rheumatology for healthcare professionals.
Cancer is considered one of the deadliest diseases globally, and continuous research is being carried out to find novel potential therapies for myriad cancer types that affect the human body. Researchers are hunting for innovative remedies to minimize the toxic effects of conventional therapies being driven by cancer, which is emerging as pivotal causes of mortality worldwide. Cancer progression s...
Computational imaging enables spatial information retrieval of objects with the use of single-pixel detectors. By combining measurements and computational methods, it is possible to reconstruct images in a variety of situations that are challenging or impossible with traditional multi-pixel cameras. However, these systems typically suffer from significant loss of imaging quality due to various noi...
OBJECTIVE: This study has developed a new automatic algorithm for the quantificationy and grading of ankylosing spondylitis (AS)-hip arthritis with ma...
This study aims to explore the clinical efficacy of arthroscopic-assisted reduction combined with robot-navigated nail placement in the treatment of t...
The diversity of diseases in rheumatology and variability in disease prevalence necessitates greater data parity in disease presentation, treatment re...
Circular RNAs (circRNAs) generally bind to RNA-binding proteins (RBPs) to play an important role in the regulation of autoimmune diseases. Thus, it is...
Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially ...
Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnost...
There has been increased excitement around the use of machine learning (ML) and artificial intelligence (AI) in dermatology for the diagnosis of skin ...
Drug combinations have exhibited promising therapeutic effects in treating cancer patients with less toxicity and adverse side effects. However, it is...
Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healt...
The accurate quantification of tumor-infiltrating immune cells turns crucial to uncover their role in tumor immune escape, to determine patient progno...
Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of...
Fibrosis is a key component in the pathogenic mechanism of a variety of diseases. These diseases involving fibrosis may share common mechanisms and th...
The paper considers the problem of handling short sets of medical data. Effectively solving this problem will provide the ability to solve numerous cl...
OBJECTIVE: Identifying pseudogout in large data sets is difficult due to its episodic nature and a lack of billing codes specific to this acute subtyp...
With advances in information technology, the demand for using data science to enhance healthcare and disease management is rapidly increasing. Among t...
Kinases form the backbone of numerous cell signaling pathways, with their dysfunction similarly implicated in multiple pathologies. Further facilitate...
Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading ...
Hepatitis C virus (HCV) contributed as a risk factor for chronic kidney disease (CKD). Many studies only showed it associated with estimated glomerula...