In this work, we developed and validated a computer method capable of robustly detecting drill breakthrough events and show the potential of deep learning-based acoustic sensing for surgical error prevention. Bone drilling is an essential part of ort...
BACKGROUND: Patients' choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital cho...
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Nov 24, 2020
The bone drilling process is characterised by various parameters, the most important of which are the feed rate (mm/s) and the drill speed (rpm). They highly reflect the final effects and results of the drilling process, such as mechanical and therma...
International journal of computer assisted radiology and surgery
Jul 11, 2020
PURPOSE: Real-time, two (2D) and three-dimensional (3D) ultrasound (US) has been investigated as a potential alternative to fluoroscopy imaging in various surgical and non-surgical orthopedic procedures. However, low signal to noise ratio, imaging ar...
AIM: To gather and compare related clinical studies, and to investigate the accuracy and reliability of deep learning in detecting orthopaedic fractures.
BACKGROUND: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up assignments might be completed by artificial intelligence (AI). We developed an AI-assisted follow-...
OBJECTIVE: To investigate the clinical effect of robot-assisted treatment of unstable pelvic fractures through a percutaneous iliac lumbar double rod fixation combined with a percutaneous pelvic anterior ring INFIX (internal fixator) fixation.
Hand loss is a catastrophic event that generates significant demands for orthopedics and prosthetics. In the course of history, prostheses evolved from passive esthetic replacements to sophisticated robotic hands. Yet, their actuation and particularl...
BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural lang...
BACKGROUND: Driven by the recent ubiquity of big data and computing power, we established the Machine Learning Arthroplasty Laboratory (MLAL) to examine and apply artificial intelligence (AI) to musculoskeletal medicine.
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