AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Pain

Showing 51 to 60 of 198 articles

Clear Filters

Efficacy of Robots-Assisted Therapy in Patients With Stroke: A Meta-analysis Update.

The Journal of cardiovascular nursing
BACKGROUND: Robot-assisted therapy (RAT) could address an unmet need to relieve the strain on healthcare providers and intensify treatment in the context of an increasing stroke incidence. A comprehensive meta-analysis could provide firmer data about...

Therapy-based expert system on function and postural stability after anterior cruciate ligament reconstruction: a pilot study.

BMC musculoskeletal disorders
PURPOSE: Wii Fit exergames have been less commonly used for the rehabilitation of athletes after Anterior Cruciate Ligament Reconstruction (ACLR). This study aims to investigate the effects of an expert system using Wii Fit exergames compared to conv...

Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation.

Scientific reports
Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. We aimed to investigate the clinical relevance of deep learning models that predict the onset of cancer pain exacerbation in hospitalized patients. We...

Early perioperative outcomes of single-port compared to multi-port robot-assisted laparoscopic partial nephrectomy.

Journal of robotic surgery
Single-port (SP) robot-assisted laparoscopic partial nephrectomy (RAPN) is a promising new technique. The aim of this study was to compare surgical and oncological outcomes of SP-RAPN to the multi-port (MP) surgical platform. This is a retrospective,...

Perioperative safety and efficacy of robot-assisted total hip arthroplasty in ERAS-managed patients: a pilot study.

Journal of orthopaedic surgery and research
AIMS: Robot-assisted total hip arthroplasty (rTHA) boasts superior accuracy in implant placement, but there is a lack of effective assessment in perioperative management in the context of enhanced recovery after surgery (ERAS). This study aimed to co...

Machine learning and EEG can classify passive viewing of discrete categories of visual stimuli but not the observation of pain.

BMC neuroscience
Previous studies have demonstrated the potential of machine learning (ML) in classifying physical pain from non-pain states using electroencephalographic (EEG) data. However, the application of ML to EEG data to categorise the observation of pain ver...

Assessment of routine same-day discharge surgery for robot-assisted radical prostatectomy.

World journal of urology
INTRODUCTION: It is important for robotic surgery to be cost-effective, especially by reducing the length of stay (LOS). Therefore, we developed a protocol for day-case robot-assisted radical prostatectomy (RARP). This study aimed to validate this as...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Scientific reports
Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign data; however, it remains uncertain whether incorporating individual patient baselines could enhance accuracy. This study aimed to investigate improvin...

Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.

Updates in surgery
Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recent years. We retrospectively analyzed the perioperative outcomes of robotic-assisted thoracoscopic surgery (RATS) with two, three, and four-hole approa...

Cooperative Learning for Personalized Context-Aware Pain Assessment From Wearable Data.

IEEE journal of biomedical and health informatics
Despite the promising performance of automated pain assessment methods, current methods suffer from performance generalization due to the lack of relatively large, diverse, and annotated pain datasets. Further, the majority of current methods do not ...