Latest AI and machine learning research in back pain for healthcare professionals.
BACKGROUND: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance, empirical research, and clinical intervention. We sought to improve existing OOD electronic phenotypes by incorporating new data types beyond diagnostic codes and by applying several statistical and machine learning methods.
Opioid use disorder (OUD) has emerged as a significant global public health issue, necessitating the discovery of new medications. In this study, we propose a deep generative model that combines a stochastic differential equation (SDE)-based diffusion model with a pretrained autoencoder. The molecular generator enables efficient generation of molecules that target multiple opioid receptors, includ...
Likely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during period...
BACKGROUND/PURPOSE: Identifying patients at risk of prolonged opioid use after surgery prompts appropriate prescription and personalized treatment pla...
BACKGROUND: Analgesia after robot assisted radical cystectomy aims to reduce postoperative pain and opioid consumption, while facilitating early mobil...
Capnography monitors trigger high priority 'no breath' alarms when CO measurements do not exceed a given threshold over a specified time-period. False...
Machine learning (ML) has emerged as a method to determine patient-specific risk for prolonged postoperative opioid use after orthopedic procedures. ...
OBJECTIVE: As the opioid epidemic continues across the United States, methods are needed to accurately and quickly identify patients at risk for opioi...
BACKGROUND:: Minimally invasive, robotic techniques for hepatobiliary procedures offer the potential for accelerated recovery and reduced opioid usage...
BACKGROUND: As opioid prescriptions have risen, there has also been an increase in opioid use disorder (OUD) and its adverse outcomes. Accurate and co...
Deep learning-enabled smartphone-based image processing has significant advantages in the development of point-of-care diagnostics. Conventionally, mo...
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models ...
BACKGROUND AND AIM: Transversus abdominis plane (TAP) block and local anesthetic infiltration (LAI) technique are used as part of the multimodal analg...
Opioid dependency has been a persistent issue in the United States over the past two decades. Increased efforts have been made to reduce opioid presc...
Industrial-based application of supercritical CO (SCCO) has emerged as a promising technology in numerous scientific fields due to offering brilliant ...
BACKGROUND: Opioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Me...
In the living cells, proteins bind small molecules (or "ligands") through a "conformational selection" mechanism, where a subset of protein structures...
To shed more light on the addictive power of the gabapentinoids (GPTs) gabapentin and pregabalin, we performed a structured face-to-face interview wit...
To identify protective and risk factors of early postoperative complications after robot-assisted radical cystectomy (RARC) for urothelial bladder ca...
OBJECTIVE: To summarize the available evidence of TAP Block in efficacy in laparoscopic or robotic hysterectomy.