AIM: The aim of the study was to develop machine learning algorithms (MLA) for diagnosing acute graft dysfunction (AGD) in kidney transplant recipients based on contrast-enhanced ultrasound (CEUS) analysis of the graft.Materials and methods: This pro...
International journal of medical informatics
Aug 30, 2024
BACKGROUND: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidity and mortality rates. However, the safety and effectiveness of using prophylactic anticoagulants for preventing DVT after spinal surgery remain cont...
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Aug 30, 2024
INTRODUCTION: Machine learning (ML) models may offer a novel solution to reducing postoperative complication rates and improving post-surgical outcomes after total joint arthroplasty (TJA). However, the variety of different ML models that exist paire...
British journal of hospital medicine (London, England : 2005)
Aug 30, 2024
The rapidly developing field of artificial intelligence (AI) may soon equip clinicians with algorithms that model and predict perioperative problems with extreme accuracy. Here, we outline emerging AI applications in preoperative risk stratification ...
British journal of hospital medicine (London, England : 2005)
Aug 30, 2024
Artificial intelligence technology has attained rapid development in recent years. The integration of artificial intelligence applications into pressure reduction mattresses, giving rise to artificial intelligence-powered pressure reduction mattress...
STUDY DESIGN: This is a retrospective cohort study utilizing machine learning to predict postoperative complications in cervical spine metastases surgery.
BACKGROUND: The purpose of this study was to develop and validate a mortality risk algorithm for pediatric surgery patients treated at KidsOR sites in 14 low- and middle-income countries.
OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preoperative ultrasonographic features. This study addresses the global rise in PTMC incidence and the cha...
OBJECTIVE: This study aimed to use machine learning (ML) to establish risk factor and prediction models of osteonecrosis of the femoral head (ONFH) in patients with femoral neck fractures (FNFs) after internal fixation.
BMC medical informatics and decision making
Aug 19, 2024
BACKGROUND: Patients with airway stenosis (AS) are associated with considerable morbidity and mortality after lung transplantation (LTx). This study aims to develop and validate machine learning (ML) models to predict AS requiring clinical interventi...