American journal of obstetrics and gynecology
38462256
BACKGROUND: Slow progression of labor is a common obstetrical problem with multiple associated complications. Tafoxiparin is a depolymerized form of heparin with a molecular structure that eliminates the anticoagulant effects of heparin. We report on...
Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a long history, starting in 1932 with R.A. Fisher and including more re...
BACKGROUND AND AIMS: Randomized controlled trials (RCTs) have reported that artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies-namely, parallel and tandem designs-have been used to evaluate the efficacy of AI-as...
CONTEXT: Motor deficits are among the most common consequences of incomplete spinal cord injury (SCI). These impairments can affect patients' levels of functioning and quality of life. Combined robotic therapy and non-invasive brain stimulation (NIBS...
The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been publishe...
European review for medical and pharmacological sciences
38375695
OBJECTIVE: This study aimed to investigate the effects of robot-assisted gait training (RAGT) on improving walking ability, and to determine the optimal dosage of task-specific training based on RAGT for stroke patients.
BACKGROUND: Robotic spinal surgery may result in better pedicle screw placement accuracy, and reduction in radiation exposure and length of stay, compared to freehand surgery. The purpose of this randomized controlled trial (RCT) is to compare screw ...
BACKGROUND: Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed and validated a multimodal artificial intelligence (MMAI) model generated from digital histopathology ...
Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules. However, to what...
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and ...