Latest AI and machine learning research in surgery for healthcare professionals.
As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, the present study compares visual mitotic counting with deep learning based automated mitotic counting and fully automated hotspot selection. Two cohort...
Performance of robot-assisted endovascular surgery (ES) remains highly dependent on an individual surgeon's skills, due to common adoption of master-slave robotic structure. Surgeons' skill modeling and unstructured surgical state perception pose prohibitive challenges for an autonomous ES robot. In this paper, a novel convolutional neural network (CNN)-based framework is proposed to address these...
A miniature resonant tactile sensor for tissue stiffness detection in robot-assisted minimally invasive surgery is proposed in this article. The propo...
BACKGROUND: Handheld laparoscopic robotized instruments have been developed to combine the advantages of a robotic operation system and conventional l...
BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for ...
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analy...
OBJECTIVE: Minimally invasive esophagectomy (MIE) has demonstrated superior outcomes compared to open approaches. The myriad of techniques has preclud...
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and postoperative patient's health. Commercially available electr...
OBJECTIVE: This case is reported to introduce an advanced surgical technique and share our experience with surgeons.
BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use c...
BACKGROUND: Soft materials, with their compliant properties, enable conformity and safe interaction with human body. With the advance in actuation and...
PURPOSE: Annotation of surgical activities becomes increasingly important for many recent applications such as surgical workflow analysis, surgical si...
OBJECTIVE: To generate a nomogram based on preoperative parameters to predict the occurrence of a major complication within 30-days of robotic partial...
BACKGROUND: Last-minute surgery cancellation represents a major wastage of resources and can cause significant inconvenience to patients. Our objectiv...
: Scientific evidence supports that prevention strategies like multicomponent physical exercise help avoiding functional decline, falls and frailty. T...
In this paper the optimum timing for the postoperative functional cure of basic intermittent exotropia is explored based on support vector machine (SV...
BACKGROUND: Computer navigation increases reproducibility compared to non-navigated total knee arthroplasty (TKA). Robotics navigation is a branch of ...
Both transcranial direct current stimulation (tDCS) and wrist robot-assisted training have demonstrated to be promising approaches for stroke rehabili...
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model fo...