Latest AI and machine learning research in nephrology for healthcare professionals.
Post-kidney transplant rejection is a critical factor influencing transplant success rates and the survival of transplanted organs. With the rapid advancement of artificial intelligence technologies, machine learning (ML) has emerged as a powerful data analysis tool, widely applied in the prediction, diagnosis, and mechanistic study of kidney transplant rejection. This mini-review systematically s...
Artificial intelligence (AI) is increasingly recognized as a transformative force in the field of solid organ transplantation. From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy, AI has the potential to improve both operational efficiency and patient outcomes. Despite these advancements, the perspectives of transplant professionals - those ...
Diabetic kidney disease (DKD), characterized by progressive renal dysfunction, is a prevalent microvascular complication of diabetes mellitus and a le...
BACKGROUND: Cancer heterogeneity results in patients with the same diagnosis responding differently to drugs, making treatments extremely challenging....
Contrast-induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventi...
BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in kidney transplant recipients (KTRs). Early identifi...
The growing demand for renewable energy has spurred the development of efficient electrochemical systems. Transition metal-based materials serve as ke...
Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided n...
Primary mitochondrial disorders are clinically and genetically heterogeneous and remain underdiagnosed in resource-limited settings. We performed a re...
Accurate toxicity assessment is essential for chemical safety, but experimental testing is costly, slow, and ethically constrained, motivating the ado...
OBJECTIVE: Chronic pulmonary embolism (CPE) and chronic thromboembolic pulmonary hypertension (CTEPH) are challenging to diagnose, with delayed detect...
BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst growth and renal decline, is the leading genetic c...
PURPOSE OF REVIEW: The degree to which computerized methods, such as artificial intelligence (AI), will aid in the assessment of kidney histopathology...
The early detection of chronic kidney disease (CKD) can lead to timely and appropriate clinical intervention. However, most CKD diagnostic systems rel...
Recent findings from the Honolulu Heart Program cohort in Hawaii suggest a longevity-associated variant of FOXO3 may provide resilience against cardio...
BACKGROUND: Sepsis recognition in the ICU remains variable and relies on consensus clinical criteria rather than biomarker-defined rules. Routine labo...
Though critical, traditional diagnostic approaches such as X-ray, CT scans, bronchoscopy and tissue biopsy don't reliably detect lung cancer at early ...
OBJECTIVES: We evaluated the data requirement for modern AI tools to outperform simpler models in predicting short-term mortality in over 500 000 pati...
INTRODUCTION: Cancer is a major global health concern, causing millions of deaths each year due to the uncontrolled growth and spread of abnormal cell...
Myostatin negatively regulates skeletal muscle size in multiple species, and therefore, myostatin blockade has been therapeutically explored to promot...