Background Artificial intelligence is an emerging technology with rapid growth and
increasing applications in orthopaedics. This study aimed to summarize the existing …

Purpose Artificial intelligence (AI) in healthcare is rapidly growing and offers novel options of
data analysis. Machine learning (ML) represents a distinct application of AI, which is capable …

Importance Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among
hospitalized patients. Personalized risk estimation and risk factor identification may allow …

Background Artificial intelligence (AI) is defined as the study of algorithms that allow
machines to reason and perform cognitive functions such as problem-solving, objects …

Background and purpose—External validation of machine learning (ML) prediction models
is an essential step before clinical application. We assessed the proportion, performance …

Purpose The number of primary total knee arthroplasties (TKA) is expected to rise
constantly. For patients and healthcare providers, the early identification of risk factors …

Background The utilization of artificial intelligence and machine learning as diagnostic and
predictive tools in perioperative medicine holds great promise. Indeed, many studies have …

Background Risk stratification plays a central role in anesthetic evaluation. The use of Big
Data and machine learning (ML) offers considerable advantages for collection and …

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 Acute kidney injury (AKI) is independently associated with morbidity and
mortality in a wide range of surgical settings. Nowadays, with the increasing use of …