The exponential growth of artificial intelligence (AI) has allowed for its integration into
multiple sectors, including, notably, healthcare. Chatbots have emerged as a pivotal …

Chronic kidney disease (CKD) poses a significant public health challenge, affecting
approximately 11% to 13% of the global population [1]. This accounts for over 800 million …

OBJECTIVE: Acute kidney injury (AKI) increases mortality and costs in hospitalized patients.
New methods for early AKI identification have been developed with targeted biomarkers and …

Objective Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP)
using machine learning (ML) and deep learning (DL). Methods In this multicentre …

Background Acute kidney injury (AKI) after coronary artery bypass grafting (CABG) surgery
is associated with poor outcomes. The objective of this study was to apply a new machine …

Children undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are prone
to developing acute kidney injury (AKI). Markers of kidney damage: kidney injury molecule …

Background: Although acute kidney injury (AKI) is a common complication in patients
undergoing hematopoietic stem cell transplantation (HSCT), its prophylaxis remains a …

Cardiothoracic surgery (CTS) is a complex and high-risk medical intervention that requires
collaboration from various specialized professionals. The integration of artificial intelligence …

Background Risk stratification and outcome prediction are crucial for intensive care resource
planning. In addressing the large data sets of intensive care unit (ICU) patients, we …

Background: Early identification of patients at high-risk of postoperative acute kidney injury
(AKI) can facilitate the development of preventive approaches. This study aimed to develop …