Latest AI and machine learning research in rheumatoid arthritis for healthcare professionals.
BACKGROUND: To improve the prediction of immune checkpoint inhibitors (ICIs) efficacy in hepatocellular carcinoma (HCC), this study categorized the tumor immune microenvironment (TIME) into two types: immune-activated (IA), characterized by a high CD8 + score and high PD-L1 combined positive score (CPS), and non-immune-activated (NIA), encompassing all other conditions. We aimed to develop an MRI-...
BACKGROUND: Diabetic macular edema (DME) is a leading cause of vision loss in diabetes, with variable responses to anti-vascular endothelial growth factor (anti-VEGF) therapy in DME patients. Current diagnosis relies on optical coherence tomography (OCT) imaging, but manual interpretation is limited. This study aims to integrate 3D-OCT features and clinical variables to develop machine learning (M...
Monitoring biomarkers offers insights for early disease (e.g., cancer, chronic diseases) screening, treatment guidance and response evaluation. To tac...
PURPOSE: Pain management after cardiac surgery is imperative, as inadequate analgesia can increase the risk of myocardial ischemia, thromboembolism, a...
PURPOSE: Some patients with neovascular age-related macular degeneration (nAMD) have persistent signs of exudation under treatment with intravitreal i...
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare setting...
Currently, the most actively investigated rapidly acting antidepressants, anxiolytics and/or anti PTSD agents, include psychedelics e.g. psilocybin, L...
The brain growth spurt (BGS) represents a pivotal window in neurodevelopment, defined by rapid neurogenesis, heightened synaptogenesis, and the dynami...
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the...
Myocardial fibrosis, a hallmark of heart failure (HF), contributes to disease progression and mortality by impairing cardiac function. Despite the ide...
Elucidating the anti-tumor role of tumor-draining lymph nodes (tdLNs) in patients could offer critical mechanistic insight and shift therapeutic strat...
The first session of the 2025 European Society of Toxicologic Pathology (ESTP) Congress reviewed routine and specialized methods for microscopic evalu...
Flavones, recognized as "privileged scaffolds" in drug discovery, hold significant promise as anti-cancer agents. This study aimed to develop a quanti...
PURPOSE: To develop a machine learning model to predict anatomical response to anti-VEGF therapy in patients with diabetic macular edema (DME).
BACKGROUND: The TCbHP regimen, consisting of combining docetaxel (T), carboplatin (Cb), trastuzumab (H), and pertuzumab (P), is the preferred neoadjuv...
Recent advances in deep learning and machine learning have greatly increased the capabilities of extracting features for evaluating the response to an...
BACKGROUND: Epilepsy is a multifaceted neurological disorder marked by seizures that can present with a wide range of symptoms. Despite the prevalent ...
Despite the growing interest in developing anti-aging drugs, high costs and low success rates of traditional drug discovery methods pose significant c...
Droplet impact, spreading and rebound was investigated experimentally on superhydrophobic laser-textured surfaces, yielding a dataset of 1498 datapoin...
Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appe...