Latest AI and machine learning research in surgery for healthcare professionals.
Untethered soft miniature robots capable of accessing hard-to-reach regions can enable new, disruptive, and minimally invasive medical procedures. However, once the control input is removed, these robots easily move from their target location because of the dynamic motion of body tissues or fluids, thereby restricting their use in many long-term medical applications. To overcome this, we propose a...
The development of valid, reliable, and objective methods of skills assessment is central to modern surgical training. Numerous rating scales have been developed and validated for quantifying surgical performance. However, many of these scoring systems are potentially flawed in their design in terms of reliability. Eye-tracking techniques, which provide a more objective investigation of the visual...
Surgical site infections (SSIs) have a major role in the evolution of medical care. Despite centuries of medical progress, the management of surgical...
The gait cycle of humans may be influenced by a range of variables, including neurological, orthopedic, and pathological conditions. Thus, gait analys...
BACKGROUND: Artificial intelligence (AI)-driven software has been developed and become commercially available within the past few years for the detect...
BACKGROUND AND AIMS: Inter-operator variations in the level of intraoperative laparoscope control by surgeons influence surgical outcomes. We aimed to...
INTRODUCTION: The transition from laparoscopic to robot-assisted procedures leads to potential increase in operative times and health care costs. Cumu...
PURPOSE: To evaluate the feasibility and accuracy of a robotic system to integrate and map computed tomography (CT) and robotic coordinates, followed ...
Esophagectomy is the gold standard for the treatment of resectable esophageal cancer. Traditionally, it is performed through a laparotomy and a thorac...
INTRODUCTION: Although rare, as the population ages, abdominal aortic aneurysm synchronous to abdominal malignancies, as renal cell carcinoma, is expe...
BACKGROUND: Deep learning models are increasingly informing medical decision making, for instance, in the detection of acute intracranial hemorrhage a...
BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and w...
This paper presents a novel approach for designing a robotic orthosis controller considering physical human-robot interaction (pHRI). Computer simulat...
BACKGROUND: Gamification applies game design elements to non-game contexts in order to engage participation and increase learner motivation. Robotic s...
INTRODUCTION: Soft robotic wearable devices, referred to as exosuits, can be a valid alternative to rigid exoskeletons when it comes to daily upper li...
This study was aimed at investigating the ultrasound based on deep learning algorithm to evaluate the rehabilitation effect of transumbilical laparosc...
PURPOSE: We investigated operative time according to procedure phases in robot-assisted laparoscopic partial nephrectomy (RAPN) and identify variables...
We used a robotic gantry to test the hypothesis that tandem running in the ant Temnothorax albipennis can be successful in the absence of trail laying...
OBJECTIVE: To explore the convolutional neural network (CNN) method in measuring hematoma volume-assisted microsurgery for spontaneous cerebral hemorr...