Latest AI and machine learning research in nephrology for healthcare professionals.
Though critical, traditional diagnostic approaches such as X-ray, CT scans, bronchoscopy and tissue ...
OBJECTIVES: We evaluated the data requirement for modern AI tools to outperform simpler models in pr...
INTRODUCTION: Cancer is a major global health concern, causing millions of deaths each year due to t...
Myostatin negatively regulates skeletal muscle size in multiple species, and therefore, myostatin bl...
OBJECTIVES: The quantitative analysis of 16-segment left ventricular wall thickness can provide insi...
BACKGROUND: This study aims to develop an interpretable machine learning model using SHapley Additiv...
BACKGROUND: The integration of multimodal single-cell data enables comprehensive organ reference atl...
Wearable surface-enhanced Raman spectroscopy (SERS) sensors can detect analytes in sweat containing ...
BACKGROUND: The prognostic significance of an adverse acid-base milieu despite venoarterial extracor...
Recent advances in artificial intelligence (AI) are revolutionizing materials science by unlocking u...
BACKGROUND: Tacrolimus is a first-line immunosuppressant essential for preventing graft rejection af...
BACKGROUND AND OBJECTIVE: Renal clear cell carcinoma (ccRCC) is highly heterogeneous, with significa...
BACKGROUND: Individuals with cardiovascular-kidney-metabolic (CKM) syndrome exhibit a substantially ...
Additive engineering in aqueous zinc-ion batteries is recognized as a key strategy for improving zin...
BACKGROUND: The molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-o...
Gastric cancer (GC) risk is shaped by environmental exposures such as benzo[a]pyrene (BaP). Here, we...
MOF-derived heteroatom-doped porous carbons hold strong potential for supercapacitor electrodes, yet...
BACKGROUND: Emerging evidence highlights the pivotal role of ferroptosis in the pathophysiology of d...
Accurate evaluation of tumor size on follow-up computed tomography (CT) scans is critical for assess...
BACKGROUND: This study aimed to develop and validate an interpretable nomogram to predict the risk o...
AIMS: Accurate stratification of mortality risk is essential for management of chronic coronary synd...