Latest AI and machine learning research in hematology for healthcare professionals.
Blood pressure (BP) management following successful reperfusion after endovascular thrombectomy (EVT) is critical in achieving favorable clinical outcomes. Individualized BP management using predictive modeling by machine learning may further improve prediction of functional outcomes. This study was a retrospective analysis of data from the Outcome in Patients Treated with Intra-Arterial Thrombect...
INTRODUCTION: Circadian rhythm disruption (CRD) is a major driver of immune dysregulation; however, whether CRD promotes ischemic stroke (IS) progression through immune imbalance and the underlying molecular mechanisms remain unclear. METHODS: Transcriptomic data from human IS brain tissues were analyzed to identify CRD associated regulators using machine-learning approaches. A CRD score model was...
This study aimed to comprehensively assess the prognostic value of routinely obtained blood-based systemic inflammatory indices in predicting all-caus...
The primary goal of variceal screening in patients with cirrhosis is to identify high-risk esophageal varices (HREV) and implement preventative measur...
OBJECTIVE: Surgical procedures involving varying tissue depths present challenges to surgeons regarding accessibility and precision, restricting instr...
PURPOSE: Placental growth factor (PGF) is associated with the progression of hepatocellular carcinoma (HCC), but current research on this relationship...
Reliable biomarkers that enable noninvasive, longitudinal assessment of disease activity and therapeutic response remain a major unmet need in inflamm...
Neutrophil extracellular traps are implicated in immunothrombosis and neuroinflammation in ischemic stroke, but blood-based markers that distinguish s...
Linezolid (LZD)-associated thrombocytopenia (TP), a type of major hematotoxicity that can lead to the discontinuation of LZD treatment in patients wit...
BACKGROUND: Perioperative anticoagulant management is critical because of the competing risks of ischemia and bleeding. Large language models (LLMs) a...
Aluminum is the second most widely used metal worldwide, with essential roles in transportation, construction, packaging, and energy infrastructure. R...
BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical challenge. Given the involvement of DNA methylation...
Steroid-induced osteonecrosis of the femoral head (SONFH) is a major cause of disability among young and middle-aged adults. However, current diagnosi...
BACKGROUND: Artificial intelligence (AI) is increasingly being implemented in digital pathology to support the tissue classification, cell detection, ...
INTRODUCTION: Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to di...
Accurate capture and molecular analysis of circulating tumor cells (CTCs) from whole blood are crucial for early cancer diagnosis, prognosis and perso...
Nanoplastics (NPs) are globally recognized as pervasive emerging contaminants with demonstrated toxicological risks, yet predicting their environmenta...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical planning, risk stratification, and outcome predict...
OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI) could identify geriatric hip-fracture patients a...
Early screening and antiviral therapy for significant liver inflammation in chronic hepatitis B (CHB) remain significant barriers as the key to diseas...