Acute kidney injury (AKI) is a serious clinical comorbidity with clear short-term and long-term
prognostic implications for inpatients. The diversity of risk factors for AKI has been …

Background The recent pandemic of CoVID-19 has emerged as a threat to global health
security. There are very few prognostic models on CoVID-19 using machine learning …

Acute kidney injury (AKI) is a common complication of hospitalization that greatly and
negatively affects the short-term and long-term outcomes of patients. Current guidelines use …

Kidney diseases form part of the major health burdens experienced all over the world.
Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great …

Background In this paper, we examine whether machine learning and deep learning can be
used to predict difficult airway intubation in patients undergoing thyroid surgery. Methods We …

Cardiac surgery-associated AKI (CSA-AKI) is common after cardiac surgery and has an
adverse impact on short-and long-term mortality. Early identification of patients at high risk of …

Purpose Machine learning (ML) is a strong candidate for making accurate predictions, as we
can use large amount of data with powerful computational algorithms. We developed a ML …

Objective In order to enhance the detection rate of multiple myeloma and execute an early
and more precise disease management, an artificial intelligence assistant diagnosis system …

Importance Despite the expansion of published prediction models for acute kidney injury
(AKI), there is little evidence of uptake of these models beyond their local derivation nor data …

Aim: We systematically review current clinical applications of artificial intelligence (AI) that
use machine learning (ML) methods for decision support in surgical oncology with an …