Healthcare systems worldwide generate vast amounts of data from many different sources.
Although of high complexity for a human being, it is essential to determine the patterns and …

In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …

Background Machine learning (ML) is increasingly being used in many areas of health care.
Its use in infection management is catching up as identified in a recent review in this journal …

An infection of the spinal epidural space, spinal epidural abscess (SEA) is a potentially
devastating entity that is rising in incidence. Its insidious presentation, variable progression …

Background Postoperative dissatisfaction after primary total knee arthroplasty (TKA) that
requires additional care or readmission may impose a significant financial burden to …

Introduction Postoperative delirium in geriatric hip fracture patients adversely affects clinical
and functional outcomes and increases costs. A preoperative prediction tool to identify high …

Purpose Preoperative prediction of mortality in femoral neck fracture patients aged 65 years
or above may be valuable in the treatment decision-making. A preoperative clinical …

Study Design: Narrative review. Objectives: This review aims to present current applications
of machine learning (ML) in spine domain to clinicians. Methods: We conducted a …

Background As the prevalence of hip osteoarthritis increases, the number of total hip
arthroplasty (THA) procedures performed is also projected to increase. Accurately risk …

As the use of machine learning algorithms in the development of clinical prediction models
has increased, researchers are becoming more aware of the deleterious effects that stem …