513 citations · 745 across the 7 of their papers we have counts for
7 papers
The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning
Alireza Borjali, Soheil Ashkani-Esfahani, Rohan Bhimani +5
Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has sh…
Emissivity Prediction of Functionalized Surfaces Using Artificial Intelligence
Greg Acosta, Andrew Reicks, Miguel Moreno +3
The radiative response of any object is governed by a surface parameter known as emissivity. Tuning the emissivity of surfaces has been of great interest in many applications invol…
Improved Diagnosis of Tibiofemoral Cartilage Defects on MRI Images Using Deep Learning
Gergo Merkely, Alireza Borjali, Molly Zgoda +5
Background: MRI is the modality of choice for cartilage imaging; however, its diagnostic performance is variable and significantly lower than the gold standard diagnostic knee arth…
Natural Language Processing with Deep Learning for Medical Adverse Event Detection from Free-Text Medical Narratives: A Case Study of Detecting Total Hip Replacement Dislocation
Alireza Borjali, Martin Magneli, David Shin +3
Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives is challenging. Natural language processing (NLP) with deep learning has already sho…
A scoping review of transfer learning research on medical image analysis using ImageNet
Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol
Objective: Employing transfer learning (TL) with convolutional neural networks (CNNs), well-trained on non-medical ImageNet dataset, has shown promising results for medical image a…
Detecting mechanical loosening of total hip replacement implant from plain radiograph using deep convolutional neural network
Alireza Borjali, Antonia F. Chen, Orhun K. Muratoglu +2
Plain radiography is widely used to detect mechanical loosening of total hip replacement (THR) implants. Currently, radiographs are assessed manually by medical professionals, whic…
Detecting total hip replacement prosthesis design on preoperative radiographs using deep convolutional neural network
Alireza Borjali, Antonia F. Chen, Orhun K. Muratoglu +2
Identifying the design of a failed implant is a key step in preoperative planning of revision total joint arthroplasty. Manual identification of the implant design from radiographi…