Neonates are not able to verbally communicate pain, hindering the correct identification of this phenomenon. Several clinical scales have been proposed to assess pain, mainly using the facial features of the neonate, but a better comprehension of the...
INTRODUCTION: Millions of people survive injuries to the central or peripheral nervous system for which neurorehabilitation is required. In addition to the physical and cognitive impairments, many neurorehabilitation patients experience pain, often n...
Upper limb lymphedema (ULLy) is an external (and/or internal) manifestation of lymphatic system insufficiency and deranged lymph transport for more than 3 months and frequently affects people as a consequence of breast cancer (BC). ULLy is often unde...
IEEE journal of biomedical and health informatics
Nov 7, 2023
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 ...
BACKGROUND: We compared surgeons' workload, physical discomfort, and neuromusculoskeletal disorders (NMSDs) across four surgical modalities: endoscopic, laparoscopic, open, and robot-assisted (da Vinci Surgical Systems).
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...
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...
Journal of orthopaedic surgery and research
Sep 18, 2023
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...
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...
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...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.